CN103997611B - Method for suppressing image fixed-pattern noise based on noise template - Google Patents
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- CN103997611B CN103997611B CN201410077941.5A CN201410077941A CN103997611B CN 103997611 B CN103997611 B CN 103997611B CN 201410077941 A CN201410077941 A CN 201410077941A CN 103997611 B CN103997611 B CN 103997611B
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Abstract
The invention relates to a digital image processing technology, in particular to a method for suppressing image fixed-pattern noise based on a noise template. The method mainly solves the technical problems that in the fixed-pattern noise suppressing process in the prior art, the integral correction is only carried out by aiming at a pixel column or a pixel block, and the differences among single pixels in the region are ignored. According to the method, the noise template of an image sensor is obtained through pre-collection; and after the sensor obtains the image, the template is utilized for performing real-time matching on the image noise, so the relevancy between image information after noise background removal and the noise template reaches the minimum.
Description
Technical field
The present invention relates to a kind of digital image processing techniques, especially relate to a kind of image stent based on noise template
The suppressing method of formula noise.
Background technology
Noise is the key factor of impact photo-sensitive cell image quality, and the acquisition of image needs through light signal collection, light
Electric conversion, the amplification of the signal of telecommunication, reading, analog digital conversion（A/D changes）Etc. process, due to the manufacture of image-forming component and reading circuit
So that imageing sensor has differences between sensitive pixel elements, this species diversity is the formation of the fixed model of image to technique
Noise (FPN, fixed pattern noise).
FPN is widely present in CMOS imageing sensor, and suppression FPN noise generally adopts common double-sampling,
Act on eliminating FPN noise by the difference of row difference amplifier and output difference amplifier in analog domain.But in simulation
The two paths of differential signals outgoing route eliminating FPN noise in domain can not be completely consistent, and therefore difference has certain error.
In addition, under the restriction of pel spacing, the design of row difference amplifier and placement are all more difficult, and its structure is relatively multiple simultaneously
Miscellaneous, more random noises can be introduced.
Fixed pattern noise described by patents such as CN101160952, CN101212562, CN101277386 eliminates
In circuit, all to eliminate row to for the purpose of the difference of photo-sensitive cell, do not solve the difference problem of single photosensitive pixel element.
A kind of fixed pattern noise suppression side of utilization image processing software is described in CN102663714A patent of invention
Method, improves the improvement of visual effect of general image by histogram equalization and nonlinear gray level mapping algorithm, this method for
The less image of signal to noise ratio, its noise suppression effect is inconspicuous.
Content of the invention
The present invention is to provide a kind of suppressing method of the image fixed pattern noise based on noise template, and it mainly solves
In the process of inhibition of the fixed pattern noise existing for prior art, do overall correction only for pixel column or block of pixels, suddenly
Omit the technical problem of difference between single pixel in region.
The above-mentioned technical problem of the present invention is mainly addressed by following technical proposals：
A kind of removing method of image fixed pattern noise of the present invention is it is characterised in that described method includes：
A. imageing sensor is placed in temperature control box, by Uniform Illumination imageing sensor, records each photosensitive pixel
The response of unit, as the fixed pattern noise template at such a temperature of this sensor；
B. fixed pattern noise template obtains in -40 DEG C to+80 DEG C temperature ranges and records；
C. using the method for dot interlace collection, the noise template at a temperature of other is obtained the collection of noise template by interpolation algorithm
?；
D., after sensor acquisition image, according to the fixed pattern noise template at a temperature of this, the noise in image is entered
Row coupling；
E. in the present invention, the process of noise matching is：Set gain and the deviator initial value of fixed pattern noise template；
F. in the present invention, the process of noise matching is：Using the gain setting and deviator, generate a width fixed pattern noise
Image, deducts this fixed pattern noise image from the real image obtaining, and calculates the image information after removing noise and fixation
The correlation coefficient of modal noise template；
G. in the present invention, the process of noise matching is：Add a knots modification in gain, repeat step f, if phase relation
Number diminishes, then continue to add this knots modification, then deduct this knots modification on the contrary, until obtaining the minima of correlation coefficient, obtains
Excellent gain coefficient；
H. in the present invention, the process of noise matching is：Add a knots modification in deviator, repeat step f, if phase relation
Number diminishes, then continue to add this knots modification, then deduct this knots modification on the contrary, until obtaining the minima of correlation coefficient, obtains
Excellent deviator coefficient；
I. it is calculated fixed pattern noise image using the optimum gain coefficient obtaining and optimum deviator coefficient, and
Deduct this fixed pattern noise image in original image, that is, obtain the image after noise suppressed；
J. in the present invention, the process of noise matching is：In order that calculating more convenient, a certain piece of area in image can be taken
Domain carries out step e to the matching operation of step h, and operation result is applied to entire image.
The present invention has the fixed pattern noise template that make use of different temperatures hypograph sensor, real-time to picture noise
Coupling, determines noise signal by calculating image information with the correlation coefficient of fixed pattern noise template, improves image imaging
Quality, is not take up hardware resource, and software is realized, and computational methods are simple, and operation time is short, the features such as possess real-time.
Brief description
Accompanying drawing 1 is a kind of principle schematic of the present invention.
Specific embodiment
Below by embodiment, and combine accompanying drawing, technical scheme is described in further detail.
Embodiment：A kind of suppressing method of image fixed pattern noise based on noise template of this example, such as Fig. 1, its step
Suddenly it is：
A. imageing sensor is placed in temperature control box, using optical integrating-sphere to imageing sensor Uniform Illumination, records
The response of each sensitive pixel elements, as the fixed pattern noise template at such a temperature of this sensor；
B. adjust the temperature of temperature control box, in -40 DEG C to+80 DEG C temperature ranges, preserve image sensing every 10 DEG C of records
Fixed pattern noise template N of device0(x, y, t), wherein x, y is respectively the horizontal and vertical pixel coordinate of image, and t is sensing
Device temperature, for the image of 384 × 288 pixels, the excursion of x is the excursion of 1 ~ 384, y is 1 ~ 288；
C., in sensor acquisition image, obtain current sensor temperature and be+23 DEG C, transfer consolidating at+20 DEG C and+30 DEG C
Mould-fixed noise template, using linear interpolation algorithm, fixed pattern noise template N at obtaining+23 DEG C0(x,y,23)；
D. gain G=0.5 and deviator B=10 of fixed pattern noise template, picture noise N (x, y, 23)=0.5 are defined
N0(x,y,23)+ 10；
E. from image information I obtaining in real time0Subtracted image noise in (x, y, 23), obtains image information I after denoising
(x, y, 23),
I(x,y,23)= I0(x, y, 23)-N (x, y, 23),
Wherein x, y define identical with step b；
F. to I (x, y, 23) and N0(x, y, 23) obtains under the conditions of gain G=0.5, deviator B=10 after doing correlation computations
Coefficient R (0.5,10)；
G., one knots modification △ G=0.05, i.e. G=0.55, B=10, meter are added on the gain G of fixed pattern noise template
Calculate R (0.55,10), whether judge R (0.55,10) less than upper one value R (0.5,10) calculating, if so, on the basis of G=0.55
Continue additional △ G=0.05；If it is not, then explanation needs to deduct △ G=0.05 on the basis of G=0.5；The like, find R (G,
10) minima, the optimal value of corresponding G is 0.7；
H. utilize same computational methods, find the minima of R (0.7, B), the optimal value of corresponding B is 25；
I. according to the optimum gain coefficient G=0.7 obtaining and optimum deviator coefficient B=25, the fixed model obtaining image is made an uproar
Sound N (x, y, 23)=0.7 N0(x, y, 23)+25, then the image after noise suppressed, I (x, y, 23)=I0(x,y,23)-
0.7·N0(x, y, 23)+25, realizes the suppression of image fixed pattern noise single pixel level.
The foregoing is only the specific embodiment of the present invention, but the architectural feature of the present invention is not limited thereto, Ren Heben
The technical staff in field in the field of the invention, all cover among the scope of the claims of the present invention by the change made or modification.
Claims (1)
1. a kind of suppressing method of the image fixed pattern noise based on noise template is it is characterised in that described method includes：
A. imageing sensor is placed in temperature control box, by Uniform Illumination imageing sensor, records each sensitive pixel elements
Response, as fixed pattern noise template under Current Temperatures for this sensor；
B. fixed pattern noise template obtains in -40 DEG C to+80 DEG C temperature ranges and records；
C. using the method for dot interlace collection, the noise template at a temperature of other is obtained the collection of noise template by interpolation algorithm；
D. after sensor acquisition image, according to the fixed pattern noise template gathering at a temperature of during image, in image
Noise is mated；
E. gain and the deviator initial value of fixed pattern noise template are set；
F. using the gain setting and deviator, generate a width fixed pattern noise image, from the real image obtaining, deduct this
Fixed pattern noise image, calculates the correlation coefficient of the image information after removing noise and fixed pattern noise template；
G., one knots modification, repeat step f are added on gain, if correlation coefficient diminishes, continues to add this knots modification, on the contrary
Then deducting this knots modification, until obtaining the minima of correlation coefficient, obtaining optimum gain coefficient；
H., one knots modification, repeat step f are added on deviator, if correlation coefficient diminishes, continues to add this knots modification, on the contrary
Then deducting this knots modification, until obtaining the minima of correlation coefficient, obtaining optimum deviator coefficient；
I. it is calculated fixed pattern noise image using the optimum gain coefficient obtaining and optimum deviator coefficient, and in original graph
Deduct this fixed pattern noise image in picture, that is, obtain the image after noise suppressed；
In order that calculating more convenient, taking a certain piece of region in image to carry out step e to the matching operation of step h, and will transport
Calculate result and be applied to entire image.
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| CN105430301B (en) * | 2014-08-26 | 2018-08-21 | 杭州海康威视数字技术股份有限公司 | Eliminate the method and its device of image sensor fixed pattern noise |
| CN106851140B (en) * | 2016-12-05 | 2019-08-20 | 宁波大学 | A method of digital photo image source identification using spatial smoothing filter |
| CN108010028B (en) * | 2017-12-27 | 2020-07-03 | 北京航空航天大学 | Fixed star detection method and device for stationary orbit satellite detector |
| CN112393804B (en) * | 2019-08-02 | 2022-04-05 | 杭州海康微影传感科技有限公司 | Image correction method and device |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6914627B1 (en) * | 1998-05-27 | 2005-07-05 | Omnivision Technologies, Inc. | Method and apparatus for digital column fixed pattern noise canceling for a CMOS image sensor |
| CN101277386A (en) * | 2007-03-28 | 2008-10-01 | 索尼株式会社 | Fixed pattern noise removal circuit and method, program, and imaging device |
| CN102768071A (en) * | 2012-07-06 | 2012-11-07 | 武汉高德红外股份有限公司 | Non-refrigerant thermal imager shutter-free nonuniformity correcting device based on template method |
| CN102968776A (en) * | 2012-11-13 | 2013-03-13 | 华中科技大学 | Linear filter and non-linear filter combined heterogeneity correction method |
| CN103335724A (en) * | 2013-06-20 | 2013-10-02 | 重庆邮电大学 | Calibration-based scene self-adaption IRFPA heterogeneity correction method |
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| JP4071157B2 (en) * | 2003-05-27 | 2008-04-02 | セイコーインスツル株式会社 | Image sensor |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6914627B1 (en) * | 1998-05-27 | 2005-07-05 | Omnivision Technologies, Inc. | Method and apparatus for digital column fixed pattern noise canceling for a CMOS image sensor |
| CN101277386A (en) * | 2007-03-28 | 2008-10-01 | 索尼株式会社 | Fixed pattern noise removal circuit and method, program, and imaging device |
| CN102768071A (en) * | 2012-07-06 | 2012-11-07 | 武汉高德红外股份有限公司 | Non-refrigerant thermal imager shutter-free nonuniformity correcting device based on template method |
| CN102968776A (en) * | 2012-11-13 | 2013-03-13 | 华中科技大学 | Linear filter and non-linear filter combined heterogeneity correction method |
| CN103335724A (en) * | 2013-06-20 | 2013-10-02 | 重庆邮电大学 | Calibration-based scene self-adaption IRFPA heterogeneity correction method |
Non-Patent Citations (1)
| Title |
|---|
| 高分辨率红外成像中的图像处理算法研究;白俊奇;《中国博士学位论文全文数据库》;20120115(第01期);第I138-70页 * |
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