CN111242863B - Method and medium for eliminating transverse chromatic aberration of lens based on image processor - Google Patents
Method and medium for eliminating transverse chromatic aberration of lens based on image processor Download PDFInfo
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Abstract
The invention provides a method and a medium for eliminating transverse chromatic aberration of a lens based on an image processor, comprising the following steps: a distortion model acquisition step: modeling the transverse chromatic aberration of the camera lens to be corrected to obtain a distortion model of the transverse chromatic aberration of the R, G and B color channels; distortion parameter acquisition: and calibrating the target camera lens to be corrected by using the checkerboard as a calibration plate to obtain distortion parameters of the transverse chromatic aberration of the three channels R, G and B of the camera lens to be corrected. According to the invention, the displacement of each pixel of the R channel and the B channel is downsampled, only 32x18x2 sample points are stored, and for a 1080P resolution camera, the storage complexity of the displacement is greatly reduced.
Description
Technical Field
The invention relates to the field of digital image processing, in particular to a method and a medium for eliminating transverse chromatic aberration of a lens based on an image processor. And more particularly, to a method for eliminating lateral chromatic aberration of a lens suitable for implementation in an image processor ASIC. Further, the invention relates to a method for implementing the elimination of the transverse chromatic aberration of the camera lens, which is suitable for implementing the ASIC of an image processor to perform the chromatic aberration correction on the RGB image and generate the RGB image after the elimination of the transverse chromatic aberration.
Background
The wavelength range of visible light is about 380 nm to 760 nm, and the refractive index of light of different wavelengths passing through the lens is also different. When visible light passes through a camera lens, the longer the wavelength of light, the greater the refractive index. For most lenses, the refractive index of blue light is the largest, and secondly, green light and red light are focused at different positions, so that the focus points of the blue light, green light and red light are shifted, and the shift is divided into a direction parallel to the focal plane and a direction perpendicular to the focal plane. The chromatic aberration caused by the displacement parallel to the focal plane direction becomes lateral chromatic aberration (lateral chromatic aberration), and the chromatic aberration caused by the displacement perpendicular to the focal plane direction becomes axial chromatic aberration (longitudinal chromatic aberrstion). The lateral chromatic aberration is most common and obvious, and along with the continuous increase of the resolution of the image sensor and the continuous decrease of the pixel size, the influence of the lateral chromatic aberration is larger and larger, so that the lateral chromatic aberration becomes a problem to be solved by a motion camera, a security monitoring camera, a vehicle recorder camera and the like.
At present, the transverse chromatic aberration of a camera lens is eliminated, and two major types of hardware solutions and software solutions exist. The hardware solution starts from a lens and eliminates lateral chromatic aberration by a plurality of lens combinations with different refractive indexes. This hardware solution adds significantly to the cost of the camera. The software method starts from the aspect of digital image processing, generally carries out polynomial fitting on transverse chromatic aberration, eliminates the transverse chromatic aberration according to solved polynomial parameters, and the fitted polynomials are high in order, and some reach 11-order high-order polynomials, so that the software is high in calculation complexity and low in instantaneity.
In the existing technology for eliminating the transverse chromatic aberration of the lens, the hardware solution method is too high in design cost and complexity, is not suitable for the use of consumer cameras, and the software solution method is high in calculation complexity and low in instantaneity, so that real-time correction processing of video images is difficult.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a method and a medium for eliminating the transverse chromatic aberration of a lens based on an image processor, which can correct the transverse chromatic aberration of a camera in real time with extremely low algorithm and hardware complexity, reduce the cost of the camera and obtain a good correction effect.
The method for eliminating the transverse chromatic aberration of the lens based on the image processor comprises the following steps:
a distortion model acquisition step: modeling the transverse chromatic aberration of the camera lens to be corrected to obtain a distortion model of the transverse chromatic aberration of the R, G and B color channels;
distortion parameter acquisition: calibrating a target camera lens to be corrected by using a checkerboard as a calibration plate to obtain distortion parameters of three paths of transverse chromatic aberration of the camera lens to be corrected R, G and B;
a displacement matrix obtaining step: according to the obtained distortion model and distortion parameters, taking a G channel as a reference, respectively calculating displacement deviation, namely a displacement matrix, R-displacment and B-displacment, of each pixel position of an R channel and a B channel on an imaging plane relative to the G channel;
and a displacement matrix sampling step: downsampling the displacement matrix of the R channel and the B channel to obtain the respective preset number of sample points of the R channel and the B channel as control vertexes for storage;
a correction structure acquisition step: a VLSI hardware structure for correcting the transverse chromatic aberration in the RGB domain is proposed;
a displacement deviation obtaining step: the hardware VLSI structure loads control vertexes of the R and B channel displacement matrixes, and upsamples the control vertexes to obtain displacement deviations of each pixel position of the R channel and the B channel on an imaging plane;
a step of eliminating transverse chromatic aberration: the hardware VLSI structure uses a bilinear interpolation method according to the displacement deviation of the R channel and the B channel, and eliminates the displacement deviation of the R channel and the B channel relative to the G channel in a progressive scanning mode, thereby eliminating the transverse chromatic aberration of the camera lens.
Preferably, the distortion model obtaining step:
modeling a camera lens lateral chromatic aberration model adopts the following model:
wherein,,
(u R-uncorrect ，v R-uncorrect )，(u G-uncorrect ，v G-uncorrect )，(u B-uncorrect ，v B-uncorrect ) Respectively obtaining pixel coordinates of three channels of uncorrected original images R, G and B;
(u R-correct ，v R-correct )，(u G-correct ，v G-correct )，(u B-correct ，v B-correct ) The pixel coordinates of three channels of corrected images R, G and B are respectively;
(u R00 ，v R00 )，(u G00 ，v G00 )，(u B00 ，v B00 ) Respectively obtaining the origin of coordinates of three channels of uncorrected original images R, G and B;
r G is the G channel pixel coordinate point and the G channel coordinate origin (u) G00 ，v G00 ) The Euclidean distance of (2) is called as the radius of the G channel pixel for short;
a 1R ，a 2R ，a 3R distortion parameters for the R channel;
a 1B ，a 2B ，a 3B the distortion parameter of the B channel;
Δr R indicating that the displacement error of the R channel is the G channel radius R G A cubic function of the function coefficient a 1R ，a 2R ，a 3R Carrying out subsequent solving;
Δr B indicating that the displacement error of the B channel is the G channel radius r G Three times of (3)A function of the function coefficient a 1B ，a 2B ，a 3B Carrying out subsequent solving;
(Δu R ，Δv R )，(Δu B ，Δv B ) The displacement deviation amounts of the transverse chromatic aberration of the R channel and the B channel are respectively;
the model is based on the following assumptions and conclusions: the lateral chromatic aberration is caused by displacement errors of focusing points of three channels R, G and B, the displacement errors are in nonlinear proportion to the radius distance between the pixel coordinates of the focusing points and the origin of coordinates of a focusing plane, and the nonlinear proportional relation can be modeled by formulas (1) and (2) to obtain a distortion model of the lateral chromatic aberration of the three channels R, G and B.
Preferably, the distortion parameter obtaining step:
using a checkerboard as a calibration plate, taking a plurality of pictures with different angles and directions by taking the corner points of the checkerboard as characteristic points to obtain a group (delta u) R ，Δv R )，(Δu B ，Δv B ) As a sample point; according to the group of sample points, combining the distortion models (1) and (2), and obtaining a distortion parameter a of the transverse chromatic aberration of the R channel and the B channel relative to the G channel based on a least square iterative optimization method 1R ，a 2R ，a 3R And a 1B ，a 2B ，a 3B ；
Preferably, the displacement matrix obtaining step:
according to the obtained distortion model and distortion parameters of the transverse chromatic aberration of the R, G and B color channels, the G channel is taken as a reference channel, and the displacement deviation, namely the displacement matrix, R-displacment and B-displacment, of each pixel position of the R channel and the B channel on an imaging plane relative to the G channel is calculated respectively;
the calculating method for calculating the displacement deviation of each pixel position of the R channel and the B channel relative to the G channel on the imaging plane comprises the following steps:
according to the calibration sample point and the transverse chromatic aberration distortion model proposed by the formula (1) and the formula (2), obtaining distortion parameters a of the R channel and the B channel by using a least square method 1R ，a 2R ，a 3R And a 1B ，a 2B ，a 3B ；
Will distort parameter a 1R ，a 2R ，a 3R And a 1B ，a 2B ，a 3B Substituting the two formulas (1) and (2) to obtain the displacement deviation (Deltau) of the R channel and B channel lateral chromatic aberration R ，Δv R ) Sum (Deltau) B ，Δv B )；
(Δu R ，Δv R ) Is the displacement deviation of the R channel relative to the G channel, namely the displacement matrix R-displacment;
(Δu B ，Δv B ) Is the displacement deviation of the B channel relative to the G channel, i.e., the displacement matrix B-displacement.
Preferably, the displacement matrix sampling step:
and non-uniform downsampling is carried out on the R-displacment and B-displament displacement matrixes, specifically, the non-uniform windowing with the size of 1080P is carried out on the images with the windowing number of 32x18, the larger the windowing is, the smaller the windowing is, and the displacement sample point at the vertex of the window is stored as the control vertex of the R channel and the B channel, so that the storage complexity is reduced.
Preferably, the correction structure obtaining step:
in the RGB domain, a VLSI hardware structure for correcting lateral chromatic aberration with low complexity and low memory consumption is proposed, and the VLSI hardware structure comprises the following 4 modules according to the data flow:
control vertex storage module: storing 32x18 control vertexes of the R channel and the B channel respectively, wherein each control vertex is a plane coordinate (u, v) subjected to hardware localization, each control vertex is 32 bits, the row coordinate u is 16 bits, the integer bit is 11 bits, and the decimal bit is 5 bits; the column coordinate v is 16 bits, the integer is 11 bits, the decimal is 5 bits, and the total memory resource of 32x18x32x2 bits, namely 4.5KB is needed;
control vertex calculation module: is responsible for calculating the current pixel point to be corrected (R uc ，G uc ，B uc ) Four control vertexes corresponding to each pixel point (R u c，G u c，B uc ) Corresponding to four control vertexes; according to the pixel point to be corrected (R uc ，G uc ，B uc ) To obtain four control vertexes around, and read the four control vertexes from the control vertex storage module, and set the pixel points (R uc ，G uc ，B uc ) The control vertexes of (a) are four vertexes a, b, c and d around the control vertex;
control vertex upsampling module: is responsible for calculating the pixel point (R) uc ，G uc ，B uc ) The amount of lateral chromatic aberration of R channel and B channel of (c) is known as the amount of lateral chromatic aberration of the pixel (R uc ，G uc ，B uc ) Coordinates (x, y) and four control vertices a, b, c, d; the coordinates of the R component of the vertices a, b, c, d are controlled to be (u) Ra ，v Ra )，(u Rb ，v Rb )，(u Rc ，v Rc ) Sum (u) Rd ，v Rd ) The method comprises the steps of carrying out a first treatment on the surface of the The coordinates of the B component of the control vertices a, B, c, d are (u) Ba ，v Ba )，(u Bb ，v Bb )，(u Bc ，v Bc ) Sum (u) Bd ，v Bd ) The preset position block can be divided into four parts according to (x, y), the normalized areas are wa, wb, wc and wd, (wa+wb+wc+wd=1), and the pixel point to be corrected (R uc ，G uc ，B uc ) The correction coordinates are found by the following formula:
R/B channel correction pixel calculation module: according to the calculated pixel point to be corrected (R uc ，G uc ，B uc ) Is a correction coordinate (u) R-correct ，v R-correct ) Sum (u) B-correct ，v B-correct ) Obtaining a pixel (R) after lateral chromatic aberration correction c ，G c ，B c ) The method comprises the steps of carrying out a first treatment on the surface of the Is embodied according to (R uc ，G uc ，B uc ) Is a correction coordinate (u) R-correct ，v R-correct ) Sum (u) B-correct ，v B-correct ) And (R) is obtained by performing 2x2 value range filtering on the pixel values in the adjacent region c ，G c ，B c ) And the lattice effect after correction of the R channel and the B channel is reduced.
Preferably, the displacement deviation obtaining step:
according to the proposed VLSI hardware structure, control vertexes of an R channel and a B channel are loaded first, and up-sampling is carried out on the control vertexes according to the position of a current pixel to be processed, so that displacement deviation of the R channel and the B channel at each pixel position is obtained.
Preferably, the lateral chromatic aberration removing step:
obtaining the corrected pixel positions of the R channel and the B channel according to the obtained displacement deviation of the R channel and the B channel at each pixel position;
and meanwhile, interpolation is carried out on pixel values of the R channel and the B channel at the correction position by using a bilinear interpolation method, so that grid effect of the corrected R channel and B channel is reduced.
According to the present invention, there is provided a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the method for eliminating lateral chromatic aberration of a lens implemented based on an image processor as described in any one of the above.
Compared with the prior art, the invention has the following beneficial effects:
the invention reduces the complexity of the transverse chromatic aberration distortion model and simplifies the polynomial fitting model which originally needs up to 11 orders into 3 orders.
According to the invention, the displacement of each pixel of the R channel and the B channel is downsampled, only 32x18x2 sample points are stored, and for a 1080P resolution camera, the storage complexity of the displacement is greatly reduced.
The invention provides a hardware VLSI realization structure, only multiplication and addition operation is needed, the hardware resource consumption is less, and the circuit realization is simple; the invention can reduce the cost of the camera lens, improve the real-time performance of processing and process the video image in real time.
Drawings
Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, given with reference to the accompanying drawings in which:
FIG. 1 is a schematic diagram of a lateral chromatic aberration of a lens processed by the present invention;
FIG. 2 is a flow chart of steps in a method and system for eliminating lateral chromatic aberration of a camera lens suitable for implementation in an ASIC of an image processor;
FIG. 3 is a schematic diagram of a calibration checkerboard and its corresponding corner points (black circles) for eliminating lateral chromatic aberration of a camera lens, which is suitable for implementation by an image processor ASIC;
FIG. 4 is a graph showing the displacement errors of the B channel (left image) and the R channel (right image) relative to the G channel for the lens lateral chromatic aberration processed by the present invention;
FIG. 5 is a schematic diagram of a non-uniform rectangular grid downsampling method and sample points for the B-channel and R-channel displacement matrices in step four of the present invention;
FIG. 6 is a schematic diagram of a hardware VLSI architecture and data flow processing according to the present invention;
FIG. 7 is a schematic diagram of a bilinear fixed-point upsampling method used in the present invention;
fig. 8 is a schematic diagram of displacement errors of a B channel (left image) and an R channel (right image) relative to a G channel after correcting a lateral chromatic aberration of a lens according to the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the present invention, but are not intended to limit the invention in any way. It should be noted that variations and modifications could be made by those skilled in the art without departing from the inventive concept. These are all within the scope of the present invention.
The method for eliminating the transverse chromatic aberration of the lens, which is suitable for being realized by an ASIC of an image processor, comprises the following steps:
a distortion model acquisition step: modeling the transverse chromatic aberration of the camera lens to be corrected to obtain a distortion model of the transverse chromatic aberration of the R, G and B color channels;
distortion parameter acquisition: calibrating a target camera lens to be corrected by using a checkerboard as a calibration plate to obtain distortion parameters of three paths of transverse chromatic aberration of the camera lens to be corrected R, G and B;
a displacement matrix obtaining step: according to the obtained distortion model and distortion parameters, taking a G channel as a reference, respectively calculating displacement deviation, namely a displacement matrix, R-displacment and B-displacment, of each pixel position of an R channel and a B channel on an imaging plane relative to the G channel;
and a displacement matrix sampling step: downsampling the displacement matrix of the R channel and the B channel to obtain the respective preset number of sample points of the R channel and the B channel as control vertexes for storage;
a correction structure acquisition step: a VLSI hardware structure for correcting the transverse chromatic aberration in the RGB domain is proposed;
a displacement deviation obtaining step: the hardware VLSI structure loads control vertexes of the R and B channel displacement matrixes, and upsamples the control vertexes to obtain displacement deviations of each pixel position of the R channel and the B channel on an imaging plane;
a step of eliminating transverse chromatic aberration: the hardware VLSI structure uses a bilinear interpolation method according to the displacement deviation of the R channel and the B channel, and eliminates the displacement deviation of the R channel and the B channel relative to the G channel in a progressive scanning mode, thereby eliminating the transverse chromatic aberration of the camera lens.
Specifically, the distortion model acquisition step:
modeling a camera lens lateral chromatic aberration model adopts the following model:
wherein,,
(u R-uncorrect ，v R-uncorrect )，(u G-uncorrect ，v G-uncorrect )，(u B-uncorrect ，v B-uncorrect ) Respectively obtaining pixel coordinates of three channels of uncorrected original images R, G and B;
(u R-correct ，v R-correct )，(u G-correct ，v G-correct )，(u B-correct ，v B-correct ) The pixel coordinates of three channels of corrected images R, G and B are respectively;
(u R00 ，v R00 )，(u G00 ，v G00 )，(u B00 ，v B00 ) Respectively obtaining the origin of coordinates of three channels of uncorrected original images R, G and B;
r G is the G channel pixel coordinate point and the G channel coordinate origin (u) G00 ，v G00 ) The Euclidean distance of (2) is called as the radius of the G channel pixel for short;
a 1R ，a 2R ，a 3R distortion parameters for the R channel;
a 1B ，a 2B ，a 3B the distortion parameter of the B channel;
Δr R indicating that the displacement error of the R channel is the G channel radius R G A cubic function of the function coefficient a 1R ，a 2R ，a 3R Carrying out subsequent solving;
Δr B indicating that the displacement error of the B channel is the G channel radius r G A cubic function of the function coefficient a 1B ，a 2B ，a 3B Carrying out subsequent solving;
(Δu R ，Δv R )，(Δu B ，Δv B ) The displacement deviation amounts of the transverse chromatic aberration of the R channel and the B channel are respectively;
the model is based on the following assumptions and conclusions: the lateral chromatic aberration is caused by displacement errors of focusing points of three channels R, G and B, the displacement errors are in nonlinear proportion to the radius distance between the pixel coordinates of the focusing points and the origin of coordinates of a focusing plane, and the nonlinear proportional relation can be modeled by formulas (1) and (2) to obtain a distortion model of the lateral chromatic aberration of the three channels R, G and B.
Specifically, the distortion parameter obtaining step:
using a checkerboard as a calibration plate, taking a plurality of pictures with different angles and directions by taking the corner points of the checkerboard as characteristic points to obtain a group (delta u) R ，Δv R )，(Δu B ，Δv B ) As a sample point; according to the group of sample points, combining the distortion models (1) and (2), and obtaining a distortion parameter a of the transverse chromatic aberration of the R channel and the B channel relative to the G channel based on a least square iterative optimization method 1R ，a 2R ，a 3R And a 1B ，a 2B ，a 3B ；
Specifically, the displacement matrix obtaining step:
according to the obtained distortion model and distortion parameters of the transverse chromatic aberration of the R, G and B color channels, the G channel is taken as a reference channel, and the displacement deviation, namely the displacement matrix, R-displacment and B-displacment, of each pixel position of the R channel and the B channel on an imaging plane relative to the G channel is calculated respectively;
the calculating method for calculating the displacement deviation of each pixel position of the R channel and the B channel relative to the G channel on the imaging plane comprises the following steps:
according to the calibration sample point and the transverse chromatic aberration distortion model proposed by the formula (1) and the formula (2), obtaining distortion parameters a of the R channel and the B channel by using a least square method 1R ，a 2R ，a 3R And a 1B ，a 2B ，a 3B ；
Will distort parameter a 1R ，a 2R ，a 3R And a 1B ，a 2B ，a 3B Substituting the two formulas (1) and (2) to obtain the displacement deviation (Deltau) of the R channel and B channel lateral chromatic aberration R ，Δv R ) Sum (Deltau) B ，Δv B )；
(Δu R ，Δv R ) Is the displacement deviation of the R channel relative to the G channel, namely the displacement matrix R-displacment;
(Δu B ，Δv B ) Is the displacement deviation of the B channel relative to the G channel, i.e. the displacement matrix B-displacement。
Specifically, the displacement matrix sampling step:
and non-uniform downsampling is carried out on the R-displacment and B-displament displacement matrixes, specifically, the non-uniform windowing with the size of 1080P is carried out on the images with the windowing number of 32x18, the larger the windowing is, the smaller the windowing is, and the displacement sample point at the vertex of the window is stored as the control vertex of the R channel and the B channel, so that the storage complexity is reduced.
Specifically, the correction structure acquisition step:
in the RGB domain, a VLSI hardware structure for correcting lateral chromatic aberration with low complexity and low memory consumption is proposed, and the VLSI hardware structure comprises the following 4 modules according to the data flow:
control vertex storage module: storing 32x18 control vertexes of the R channel and the B channel respectively, wherein each control vertex is a plane coordinate (u, v) subjected to hardware localization, each control vertex is 32 bits, the row coordinate u is 16 bits, the integer bit is 11 bits, and the decimal bit is 5 bits; the column coordinate v is 16 bits, the integer is 11 bits, the decimal is 5 bits, and the total memory resource of 32x18x32x2 bits, namely 4.5KB is needed;
control vertex calculation module: is responsible for calculating the current pixel point to be corrected (R uc ，G uc ，B uc ) Four control vertexes corresponding to each pixel point (R uc ，G uc ，B uc ) Corresponding to four control vertexes; according to the pixel point to be corrected (R uc ，G uc ，B uc ) To obtain four control vertexes around, and read the four control vertexes from the control vertex storage module, and set the pixel points (R uc ，G uc ，B uc ) The control vertexes of (a) are four vertexes a, b, c and d around the control vertex;
control vertex upsampling module: is responsible for calculating the pixel point (R) uc ，G uc ，B uc ) The amount of lateral chromatic aberration of R channel and B channel of (c) is known as the amount of lateral chromatic aberration of the pixel (R uc ，G uc ，B uc ) Coordinates (x, y) and four controlsPreparing vertexes a, b, c and d; the coordinates of the R component of the vertices a, b, c, d are controlled to be (u) Ra ，v Ra )，(u Rb ，v Rb )，(u Rc ，v Rc ) Sum (u) Rd ，v Rd ) The method comprises the steps of carrying out a first treatment on the surface of the The coordinates of the B component of the control vertices a, B, c, d are (u) Ba ，v Ba )，(u Bb ，v Bb )，(u Bc ，v Bc ) Sum (u) Bd ，v Bd ) The preset position block can be divided into four parts according to (x, y), the normalized areas are wa, wb, wc and wd, (wa+wb+wc+wd=1), and the pixel point to be corrected (R uc ，G uc ，B uc ) The correction coordinates are found by the following formula:
R/B channel correction pixel calculation module: according to the calculated pixel point to be corrected (R uc ，G uc ，B uc ) Is a correction coordinate (u) R-correct ，v R-correct ) Sum (u) B-correct ，v B-correct ) Obtaining a pixel (R) after lateral chromatic aberration correction c ，G c ，B c ) The method comprises the steps of carrying out a first treatment on the surface of the Is embodied according to (R uc ，G uc ，B uc ) Is a correction coordinate (u) R-correct ，v R-correct ) Sum (u) B-correct ，v B-correct ) And (R) is obtained by performing 2x2 value range filtering on the pixel values in the adjacent region c ，G c ，B c ) And the lattice effect after correction of the R channel and the B channel is reduced.
Specifically, the displacement deviation obtaining step:
according to the proposed VLSI hardware structure, control vertexes of an R channel and a B channel are loaded first, and up-sampling is carried out on the control vertexes according to the position of a current pixel to be processed, so that displacement deviation of the R channel and the B channel at each pixel position is obtained.
Specifically, the lateral chromatic aberration removing step:
obtaining the corrected pixel positions of the R channel and the B channel according to the obtained displacement deviation of the R channel and the B channel at each pixel position;
and meanwhile, interpolation is carried out on pixel values of the R channel and the B channel at the correction position by using a bilinear interpolation method, so that grid effect of the corrected R channel and B channel is reduced.
According to the present invention, there is provided a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the method for eliminating lateral chromatic aberration of a lens implemented based on an image processor as described in any one of the above.
The present invention will be described more specifically by way of preferred examples.
Preferred example 1:
an implementation method and system for eliminating camera lens lateral chromatic aberration (lateral chromatic aberration) suitable for being implemented by an image processor ASIC, as shown in FIG. 2, comprises the following steps:
modeling the transverse chromatic aberration of a camera lens to be corrected to obtain a distortion model of the transverse chromatic aberration of three color channels R, G and B; FIG. 1 is a schematic diagram of lateral chromatic aberration of a lens;
secondly, calibrating a target camera lens to be corrected by using a checkerboard as a calibration plate to obtain distortion parameters of transverse chromatic aberration of three channels R, G and B of the camera lens to be corrected; as shown in fig. 3, a calibration checkerboard for eliminating the lateral chromatic aberration of a camera lens and a schematic diagram of corresponding angular points (round black points) are suitable for being realized by an image processor ASIC;
calculating displacement deviation, namely a displacement matrix, R-displacment and B-displacment, of each pixel position of the R channel and the B channel on an imaging plane relative to the G channel by using the distortion model and distortion parameters and taking the G channel as a reference; as shown in fig. 4, the displacement error of the B channel (left image) and the R channel (right image) with respect to the G channel is schematically shown for the lateral chromatic aberration of the lens processed by the present invention;
step four, downsampling the displacement matrix of the R channel and the B channel to obtain 32x18 sample points of the R channel and the B channel respectively, and storing the sample points as control vertexes; as shown in fig. 5, step five of the non-uniform rectangular grid downsampling method and sample point schematic diagram of the B-channel and R-channel displacement matrix proposes a VLSI hardware structure for correcting lateral chromatic aberration in the RGB domain;
loading control vertexes of the R and B channel displacement matrixes by a hardware VLSI structure, and up-sampling the control vertexes to obtain displacement deviations of each pixel position of the R channel and the B channel on an imaging plane; FIG. 6 is a schematic diagram of a hardware VLSI structure and data flow processing according to the present invention;
and seventhly, the hardware VLSI structure eliminates the displacement deviation of the R channel and the B channel relative to the G channel in a progressive scanning mode by using a bilinear interpolation method according to the displacement deviation of the R channel and the B channel, and eliminates the transverse chromatic aberration of a camera lens. FIG. 7 is a schematic diagram of a bilinear fixed-point upsampling method used in the present invention.
In the first step, modeling the camera lens lateral chromatic aberration model adopts the following model:
(u R-uncorrect ，v R-uncorrect )，(u G-uncorrect ，v c-uncorrect )，(u B-uncorrect ，v B-uncorrect ) Respectively obtaining pixel coordinates of three channels of uncorrected original images R, G and B; (u) R-correct ，v R-correct )，(u G-correct ，v G-correct )，(u B-correct ，v B-correct ) The pixel coordinates of three channels of corrected images R, G and B are respectively; (u) R00 ，v R00 )，(u G00 ，v G00 )，(u B00 ，v B00 ) Three channels of uncorrected original images R, G and B respectivelyA coordinate origin; r is (r) G Is the G channel pixel coordinate point and the G channel coordinate origin (u) G00 ，v G00 ) The Euclidean distance of (2) is called as the radius of the G channel pixel for short; a, a 1R ，a 2R ，a 3R Distortion parameters for the R channel; a, a 1B ，a 2B ，a 3B The distortion parameter of the B channel; (Deltau) R ，Δv R )，(Δu B ，Δv B ) The displacement deviation amounts of the transverse chromatic aberration of the R channel and the B channel are respectively; the model is based on the following assumptions and conclusions: the lateral chromatic aberration is caused by displacement errors of focusing points of three channels R, G and B, and the displacement errors are in nonlinear proportion to the radius distance between the pixel coordinates of the focusing point and the origin of coordinates of a focusing plane, and the nonlinear proportional relation can be modeled by formulas (1) and (2).
In the second step, a checkerboard is used as a calibration plate, the corner points of the checkerboard are used as characteristic points, a plurality of pictures with different angles and orientations are shot, and a group of (Deltau) is obtained R ，Δv R )，(Δu B ，Δv B ) As a sample point; according to the group of sample points, combining the distortion models (1) and (2), and obtaining a distortion parameter a of the transverse chromatic aberration of the R channel and the B channel relative to the G channel based on a least square iterative optimization method 1R ，a 2R ，a 3R And a 1B ，a 2B ，a 3B ；
In the third step, according to the distortion model and parameters of the R, G and B channels, the G channel is a reference channel, and displacement deviation, namely displacement matrix, R-displacment and B-displacment, of each pixel position of the R channel and the B channel on an imaging plane relative to the G channel is calculated respectively;
in the fourth step, the R-displacement matrix and the B-displacement matrix are non-uniformly downsampled, specifically, the non-uniform window with the window number of 32x18 is divided up and down, the larger the window is, the smaller the window is, and the displacement sample point at the vertex of the window is stored as the control vertex of the R and B channels, so as to reduce the storage complexity.
In step five, a VLSI hardware architecture for correcting lateral chromatic aberration with low complexity and low memory consumption is proposed in the RGB domain.
In the sixth step, the VLSI hardware structure loads the vertex-to-vertex position control module of the displacement matrix of the R and B channels in the fourth step, and in the processing process, upsamples the vertex according to the current position of the pixel to be processed, thereby obtaining the displacement deviation of the R channel and the B channel at each pixel position, and saving a large amount of storage resources.
In the seventh step, the corrected pixel positions of the R channel and the B channel are obtained according to the displacement deviation of the R channel and the B channel; and meanwhile, interpolation is carried out on pixel values of the R channel and the B channel at the correction position by using a bilinear interpolation method, so that grid effect of the corrected R channel and B channel is reduced. Fig. 8 is a schematic diagram of displacement errors of a B channel (left image) and an R channel (right image) relative to a G channel after correcting the lateral chromatic aberration of the lens according to the present invention.
In the description of the present application, it should be understood that the terms "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate orientations or positional relationships based on the orientations or positional relationships illustrated in the drawings, merely to facilitate description of the present application and simplify the description, and do not indicate or imply that the devices or elements being referred to must have a specific orientation, be configured and operated in a specific orientation, and are not to be construed as limiting the present application.
Those skilled in the art will appreciate that the systems, apparatus, and their respective modules provided herein may be implemented entirely by logic programming of method steps such that the systems, apparatus, and their respective modules are implemented as logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc., in addition to the systems, apparatus, and their respective modules being implemented as pure computer readable program code. Therefore, the system, the apparatus, and the respective modules thereof provided by the present invention may be regarded as one hardware component, and the modules included therein for implementing various programs may also be regarded as structures within the hardware component; modules for implementing various functions may also be regarded as being either software programs for implementing the methods or structures within hardware components.
The foregoing describes specific embodiments of the present invention. It is to be understood that the invention is not limited to the particular embodiments described above, and that various changes or modifications may be made by those skilled in the art within the scope of the appended claims without affecting the spirit of the invention. The embodiments of the present application and features in the embodiments may be combined with each other arbitrarily without conflict.
Claims (8)
1. The method for eliminating the transverse chromatic aberration of the lens based on the image processor is characterized by comprising the following steps:
a distortion model acquisition step: modeling the transverse chromatic aberration of the camera lens to be corrected to obtain a distortion model of the transverse chromatic aberration of the R, G and B color channels;
distortion parameter acquisition: calibrating a target camera lens to be corrected by using a checkerboard as a calibration plate to obtain distortion parameters of three paths of transverse chromatic aberration of the camera lens to be corrected R, G and B;
a displacement matrix obtaining step: according to the obtained distortion model and distortion parameters, taking a G channel as a reference, respectively calculating displacement deviation, namely a displacement matrix, R-displacment and B-displacment, of each pixel position of an R channel and a B channel on an imaging plane relative to the G channel;
and a displacement matrix sampling step: downsampling the displacement matrix of the R channel and the B channel to obtain the respective preset number of sample points of the R channel and the B channel as control vertexes for storage;
a correction structure acquisition step: a VLSI hardware structure for correcting the transverse chromatic aberration in the RGB domain is proposed;
a displacement deviation obtaining step: the hardware VLSI structure loads control vertexes of the R and B channel displacement matrixes, and upsamples the control vertexes to obtain displacement deviations of each pixel position of the R channel and the B channel on an imaging plane;
a step of eliminating transverse chromatic aberration: the hardware VLSI structure uses a bilinear interpolation method according to the displacement deviation of the R channel and the B channel, and eliminates the displacement deviation of the R channel and the B channel relative to the G channel in a progressive scanning mode, and eliminates the transverse chromatic aberration of a camera lens;
the correction structure acquisition step:
in the RGB domain, a VLSI hardware structure for correcting lateral chromatic aberration with low complexity and low memory consumption is proposed, and the VLSI hardware structure comprises the following 4 modules according to the data flow:
control vertex storage module: storing 32x18 control vertexes of the R channel and the B channel respectively, wherein each control vertex is a plane coordinate (u, v) subjected to hardware localization, each control vertex is 32 bits, the row coordinate u is 16 bits, the integer bit is 11 bits, and the decimal bit is 5 bits; the column coordinate v is 16 bits, the integer is 11 bits, the decimal is 5 bits, and the total memory resource of 32x18x32x2 bits, namely 4.5KB is needed;
control vertex calculation module: is responsible for calculating the current pixel point to be corrected (R uc ，G uc ，B uc ) Four control vertexes corresponding to each pixel point (R uc ，G uc ，B uc ) Corresponding to four control vertexes; according to the pixel point to be corrected (R uc ，G uc ，B uc ) To obtain four control vertexes around, and read the four control vertexes from the control vertex storage module, and set the pixel points (R uc ，G uc ，B uc ) The control vertexes of (a) are four vertexes a, b, c and d around the control vertex;
control vertex upsampling module: is responsible for calculating the pixel point (R) uc ，G uc ，B uc ) The amount of lateral chromatic aberration of R channel and B channel of (c) is known as the amount of lateral chromatic aberration of the pixel (R uc ，G uc ，B uc ) Coordinates (x, y) and four control vertices a, b, c, d; the coordinates of the R component of the vertices a, b, c, d are controlled to be (u) Ra ，v Ra )，(u Rb ，v Rb )，(u Rc ，v Rc ) Sum (u) Rd ，v Rd ) The method comprises the steps of carrying out a first treatment on the surface of the The coordinates of the B component of the control vertices a, B, c, d are (u) Ba ，v Ba )，(u Bb ，v Bb )，(u Bc ，v Bc ) Sum (u) Bd ，v Bd ) Can be preset according to (x, y)The position block is divided into four parts, the normalized areas are wa, wb, wc and wd, (wa+wb+wc+wd=1), and the pixel point to be corrected (R uc ，G uc ，B uc ) The correction coordinates are found by the following formula:
R/B channel correction pixel calculation module: according to the calculated pixel point to be corrected (R uc ，G uc ，B uc ) Is a correction coordinate (u) R-correct ，v R-correct ) Sum (u) B-correct ，v B-correct ) Obtaining a pixel (R) after lateral chromatic aberration correction c ，G c ，B c ) The method comprises the steps of carrying out a first treatment on the surface of the Is embodied according to (R uc ，G uc ，B uc ) Is a correction coordinate (u) R-correct ，v R-correct ) Sum (u) B-correct ，v B-correct ) And (R) is obtained by performing 2x2 value range filtering on the pixel values in the adjacent region c ，G c ，B c ) And the lattice effect after correction of the R channel and the B channel is reduced.
2. The method for eliminating lateral chromatic aberration of a lens based on implementation of an image processor according to claim 1, wherein the distortion model obtaining step:
modeling a camera lens lateral chromatic aberration model adopts the following model:
wherein,,
(u R-uncorrect ，v R-uncorrect )，(u G-uncorrect ，v G-uncorrect )，(u B-uncorrect ，v B-uncorrect ) Respectively obtaining pixel coordinates of three channels of uncorrected original images R, G and B;
(u R-correct ，v R-correct )，(u G-correct ，v G-correct )，(u B-correct ，v B-correct ) The pixel coordinates of three channels of corrected images R, G and B are respectively;
(u R00 ，v R00 )，(u G00 ，v G00 )，(u B00 ，v B00 ) Respectively obtaining the origin of coordinates of three channels of uncorrected original images R, G and B;
r G is the G channel pixel coordinate point and the G channel coordinate origin (u) G00 ，v G00 ) The Euclidean distance of (2) is called as the radius of the G channel pixel for short;
a 1R ，a 2R ，a 3R distortion parameters for the R channel;
a 1B ，a 2B ，a 3B the distortion parameter of the B channel;
Δr R indicating that the displacement error of the R channel is the G channel radius R G A third order function of the distortion parameter a 1R ，a 2R ，a 3R Carrying out subsequent solving;
Δr B indicating that the displacement error of the B channel is the G channel radius r G A third order function of the distortion parameter a 1B ，a 2B ，a 3B Carrying out subsequent solving;
(Δu R ，Δv R )，(Δu B ，Δv B ) The displacement deviation amounts of the transverse chromatic aberration of the R channel and the B channel are respectively;
the model is based on the following assumptions and conclusions: the lateral chromatic aberration is caused by displacement errors of focusing points of three channels R, G and B, the displacement errors are in nonlinear proportion to the radius distance between the pixel coordinates of the focusing points and the origin of coordinates of a focusing plane, and the nonlinear proportional relation can be modeled by formulas (1) and (2) to obtain a distortion model of the lateral chromatic aberration of the three channels R, G and B.
3. The method for eliminating lateral chromatic aberration of a lens based on implementation of an image processor according to claim 2, wherein the distortion parameter obtaining step:
using a checkerboard as a calibration plate, taking a plurality of pictures with different angles and directions by taking the corner points of the checkerboard as characteristic points to obtain a group (delta u) R ，Δv R )，(Δu B ，Δv B ) As a sample point; according to the group of sample points, combining the distortion models (1) and (2), and obtaining a distortion parameter a of the transverse chromatic aberration of the R channel and the B channel relative to the G channel based on a least square iterative optimization method 1R ，a 2R ，a 3R And a 1B ，a 2B ，a 3B 。
4. A method for eliminating lateral chromatic aberration of a lens based on implementation of an image processor as defined in claim 3, wherein the displacement matrix obtaining step:
according to the obtained distortion model and distortion parameters of the transverse chromatic aberration of the R, G and B color channels, the G channel is taken as a reference channel, and the displacement deviation, namely the displacement matrix, R-displacment and B-displacment, of each pixel position of the R channel and the B channel on an imaging plane relative to the G channel is calculated respectively;
the calculating method for calculating the displacement deviation of each pixel position of the R channel and the B channel relative to the G channel on the imaging plane comprises the following steps:
according to the calibration sample point and the transverse chromatic aberration distortion model proposed by the formula (1) and the formula (2), obtaining distortion parameters a of the R channel and the B channel by using a least square method 1R ，a 2R ，a 3R And a 1B ，a 2B ，a 3B ；
Will distort parameter a 1R ，a 2R ，a 3R And a 1B ，a 2B ，a 3B Substituting the two formulas (1) and (2) to obtain the displacement deviation (Deltau) of the R channel and B channel lateral chromatic aberration R ，Δv R ) Sum (Deltau) B ，Δv B )；
(Δu R ，Δv R ) Is the displacement deviation of the R channel relative to the G channel, namely the displacement matrix R-displacment;
(Δu B ，Δv B ) Is the displacement deviation of the B channel relative to the G channel, i.e., the displacement matrix B-displacement.
5. The method for eliminating lateral chromatic aberration of a lens based on implementation of an image processor of claim 4, wherein the displacement matrix sampling step:
and non-uniform downsampling is carried out on the R-displacment and B-displament displacement matrixes, specifically, the non-uniform windowing with the size of 1080P is carried out on the images with the windowing number of 32x18, the larger the windowing is, the smaller the windowing is, and the displacement sample point at the vertex of the window is stored as the control vertex of the R channel and the B channel, so that the storage complexity is reduced.
6. The method for eliminating lateral chromatic aberration of a lens based on implementation of an image processor according to claim 1, wherein the displacement deviation obtaining step:
according to the proposed VLSI hardware structure, control vertexes of an R channel and a B channel are loaded first, and up-sampling is carried out on the control vertexes according to the position of a current pixel to be processed, so that displacement deviation of the R channel and the B channel at each pixel position is obtained.
7. The method for eliminating lateral chromatic aberration of a lens based on implementation of an image processor as defined in claim 6, wherein the lateral chromatic aberration eliminating step:
obtaining the corrected pixel positions of the R channel and the B channel according to the obtained displacement deviation of the R channel and the B channel at each pixel position;
and meanwhile, interpolation is carried out on pixel values of the R channel and the B channel at the correction position by using a bilinear interpolation method, so that grid effect of the corrected R channel and B channel is reduced.
8. A computer-readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the steps of the method for eliminating lateral chromatic aberration of a lens implemented based on an image processor as claimed in any one of claims 1 to 7.
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| WO2024013405A1 (en) * | 2022-07-13 | 2024-01-18 | Jj Gestión Integral S.L. | Method for reducing lateral chromatic aberration on a screen by viewing through lenses, and device for said method |
| CN115499629B (en) * | 2022-08-31 | 2023-05-26 | 北京奕斯伟计算技术股份有限公司 | Lateral chromatic aberration correction method, device, equipment and storage medium |
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2306397A1 (en) * | 2009-10-01 | 2011-04-06 | Thomson Licensing | Method and system for optimizing lens aberration detection |
| JP2012257265A (en) * | 2012-07-13 | 2012-12-27 | Canon Inc | Image processing apparatus and image processing method |
| WO2014132096A1 (en) * | 2013-02-26 | 2014-09-04 | Nintendo European Research And Development | Block color conversion |
| EP2938058A1 (en) * | 2014-04-25 | 2015-10-28 | Canon Kabushiki Kaisha | Image processing apparatus that performs image restoration processing and image processing method |
| EP3093818A2 (en) * | 2015-05-11 | 2016-11-16 | Canon Kabushiki Kaisha | Image processing apparatus that performs image restoration processing, method of controlling the same, and storage medium |
| CN106485720A (en) * | 2016-11-03 | 2017-03-08 | 广州视源电子科技股份有限公司 | Image processing method and device |
| EP3276944A1 (en) * | 2016-07-28 | 2018-01-31 | Canon Kabushiki Kaisha | Image processing apparatus, image capturing apparatus, image processing method, and image processing program |
| WO2018137773A1 (en) * | 2017-01-27 | 2018-08-02 | Sony Mobile Communications Inc | Method and device for blind correction of lateral chromatic aberration in color images |
-
2020
- 2020-01-09 CN CN202010022469.0A patent/CN111242863B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2306397A1 (en) * | 2009-10-01 | 2011-04-06 | Thomson Licensing | Method and system for optimizing lens aberration detection |
| JP2012257265A (en) * | 2012-07-13 | 2012-12-27 | Canon Inc | Image processing apparatus and image processing method |
| WO2014132096A1 (en) * | 2013-02-26 | 2014-09-04 | Nintendo European Research And Development | Block color conversion |
| EP2938058A1 (en) * | 2014-04-25 | 2015-10-28 | Canon Kabushiki Kaisha | Image processing apparatus that performs image restoration processing and image processing method |
| EP3093818A2 (en) * | 2015-05-11 | 2016-11-16 | Canon Kabushiki Kaisha | Image processing apparatus that performs image restoration processing, method of controlling the same, and storage medium |
| EP3276944A1 (en) * | 2016-07-28 | 2018-01-31 | Canon Kabushiki Kaisha | Image processing apparatus, image capturing apparatus, image processing method, and image processing program |
| CN106485720A (en) * | 2016-11-03 | 2017-03-08 | 广州视源电子科技股份有限公司 | Image processing method and device |
| WO2018137773A1 (en) * | 2017-01-27 | 2018-08-02 | Sony Mobile Communications Inc | Method and device for blind correction of lateral chromatic aberration in color images |
Non-Patent Citations (2)
| Title |
|---|
| Julie Klein and Johannes Brauers and Til Aach.Spatial and Spectral Analysis and Modeling of Transversal Chromatic Aberrations and their Compensation.《Conference on Colour in Graphics》.2010,516-522. * |
| Micah K. Johnson.Exposing Digital Forgeries Through Chromatic Aberration.Workshop on Multmedia & tampering.2006,全文. * |
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