CN104299600B - Image display device and image optimization method thereof - Google Patents

Abstract

An image display device and an image optimization method thereof. The image display apparatus includes an image content analyzer, a brightness compensator, and an image optimization processor. The image content analyzer receives the image data and the ambient light brightness, and generates a backlight brightness adjustment value according to the image data and the ambient light brightness. The brightness compensator generates an image data brightness adjustment value according to the backlight brightness adjustment value, and adjusts the brightness of the image data according to the image data brightness adjustment value to generate first image data. The image optimization processor generates a saturation adjustment weight according to the brightness adjustment value of the image data. The image optimization processor adjusts the brightness of the first image data according to the saturation adjustment weight to generate output image data.

Description

Image display device and image optimization method thereof

technical field

The invention relates to an image display device, and in particular to an image display device capable of image optimization.

Background technique

With the increasing popularity of electronic products, providing high-quality display devices on electronic devices has become an important issue for designers. In order to meet the demands of the mobility of electronic devices, users need electronic devices that can provide high-quality display in any environment.

In the known technical field, the display device can adjust the brightness generated by the backlight module according to the ambient brightness of the environment. However, in a relatively bright outdoor environment, in order to resist the reflection effect of strong light, the brightness generated by the backlight module is often adjusted to the maximum brightness, resulting in waste of power consumption. In addition, in order to effectively save power consumption, the display device in the prior art can moderately reduce the brightness generated by the backlight module by increasing the brightness of the displayed image.

However, simply increasing the brightness of the displayed image will cause the quality of the displayed image to deteriorate, such as increased noise and color distortion, which will affect the visual effect presented by the display device. Therefore, how to balance display quality and power consumption is a problem that designers in the field pay attention to.

Contents of the invention

The present invention provides an image display device, which can perform an image optimization operation on image data after brightness adjustment, so as to improve display quality.

The present invention also provides an image optimization method suitable for an image display device, which can perform image optimization actions on image data after brightness adjustment, so as to improve display quality.

The image display device of the present invention includes an image content analyzer, a brightness compensator and an image optimization processor. The image content analyzer receives image data and ambient light brightness, and generates a backlight brightness adjustment value according to the image data and ambient light brightness. The brightness compensator is coupled to the image content analyzer, and generates image data brightness adjustment values according to the backlight brightness adjustment value, and adjusts brightness of the image data according to the image data brightness adjustment value to generate first image data. The image optimization processor is coupled to the brightness compensator, and generates saturation adjustment weights according to the brightness adjustment value of the image data. The image optimization processor adjusts the brightness of the first image data according to the saturation adjustment weight to generate output image data.

In an embodiment of the present invention, the above-mentioned image optimization processor further calculates the brightness increase between the output image data and the first image data, and calculates the detail variation of the output image data. The image optimization processor adjusts the output image data according to the brightness increase and the detail variation to generate the adjusted output image data.

In an embodiment of the present invention, the above-mentioned image optimization processor calculates a brightness difference between the output image data and the first image data to obtain a brightness increase.

In an embodiment of the present invention, the above-mentioned output image data includes a plurality of pixel data. The image optimization processor calculates the difference between the brightness values of each pixel data and a plurality of adjacent pixel data adjacent to each pixel data to obtain detail variation.

In an embodiment of the present invention, the above-mentioned image optimization processor obtains the brightness correction weight value according to the brightness increase and the brightness increase weight function. The image optimization processor obtains the detail variation correction weight value according to the detail variation degree and the detail variation weight function.

In an embodiment of the present invention, the above-mentioned image optimization processor obtains the detail correction weight according to the sum of the brightness correction weight value and the detail variation correction weight value. The image optimization processor adjusts the output image data according to the detail correction weight to generate the adjusted output image data.

In an embodiment of the present invention, the above-mentioned image optimization processor generates the saturation adjustment weight according to the saturation adjustment weight function and the brightness adjustment value of the image data. Wherein, the saturation adjustment weight is inversely proportional to the brightness adjustment value of the image data.

The image optimization method of the present invention is applicable to image display devices. The steps include: receiving image data and ambient light brightness, and generating a backlight brightness adjustment value according to the image data and ambient light brightness; generating an image data brightness adjustment value according to the backlight brightness adjustment value, and adjusting according to the image data brightness adjustment value The brightness of the image data is used to generate the first image data; and the saturation adjustment weight is generated according to the brightness adjustment value of the image data, and the brightness of the first image data is adjusted according to the saturation adjustment weight to generate the output image data.

Based on the above, the image display device of the present invention further adjusts the brightness of the image data according to the adjustment of the brightness of the backlight, and adds an action of adjusting the saturation of the adjusted image data to further optimize the image to be displayed and improve the image display device. display performance.

In order to make the above-mentioned features and advantages of the present invention more comprehensible, the following specific embodiments are described in detail with reference to the accompanying drawings.

Description of drawings

FIG. 1 is a schematic diagram of an image display device 100 according to an embodiment of the present invention.

FIG. 2 is a graph illustrating a saturation adjustment weight function according to an embodiment of the present invention.

FIG. 3 is a schematic diagram of a brightness increasing weight function according to an embodiment of the present invention.

FIG. 4 is a schematic diagram of a detailed variation weight function according to an embodiment of the present invention.

FIG. 5 is a flowchart of an image optimization method according to an embodiment of the present invention.

【Symbol Description】

100: image display device

110: Image Content Analyzer

120: Brightness Compensator

130: Image optimization processor

ENL: ambient light level

BLT: Backlight brightness adjustment value

IMG1: first image data

IMGD: image data

IMGO: output image data

dY: brightness adjustment value

210～230, 310, 410: curve

S510～S530: image optimization steps

detailed description

Please refer to FIG. 1 , which is a schematic diagram of an image display device 100 according to an embodiment of the present invention. The image display device 100 includes an image content analyzer 110 , a brightness compensator 120 and an image optimization processor 130 . The image content analyzer 110 receives the image data IMGD and the ambient light level ENL. The image content analyzer 110 generates a backlight brightness adjustment value BLT according to the image data IMGD and the ambient light brightness ENL.

The backlight brightness adjustment value BLT is sent to the brightness compensator 120 coupled to the image content analyzer 110 . The brightness compensator 120 generates an image data brightness adjustment value and an image data brightness adjustment ratio according to the backlight brightness adjustment value BLT. The brightness compensator 120 adjusts the brightness of the image data IMGD according to the image data brightness adjustment value and the image data brightness adjustment ratio to generate the first image data IMG1. For example, taking the image data IMGD including the first color image data RIN, the second color image data GIN and the third color image data BIN as an example, the brightness compensator 120 generates image data brightness adjustment according to the backlight brightness adjustment value BLT. The value dY and the brightness adjustment ratio RATIO of the image data are used to generate the first image data IMG1 including the first color image data RIN1 , the second color image data GIN1 and the third color image data BIN1 . Wherein, the calculation method of the first color light image data RIN1, the second color light image data GIN1 and the third color light image data BIN1 is shown in the following formula (1):

RIN1＝RATIO×RIN+dY

GIN1=RATIO×GIN+dY

BIN1＝RATIO×BIN+dY (1)

Taking the backlight brightness adjustment value BLT as an example to reduce the backlight brightness of the image display device 100 , the image data brightness adjustment ratio RATIO may be a value greater than 1 and used to increase the brightness of the image data IMGD to generate the first image data IMG1 . The image data brightness adjustment value dY can be used to determine whether to adjust the saturation of the image data IMGD. Wherein, when the image data brightness adjustment value dY is greater than 0, it means that the saturation of the image data IMGD will be lowered; when the image data brightness adjustment value dY is less than 0, it means that the saturation of the image data IMGD will be increased; and when When the image data brightness adjustment value dY is equal to 0, it means that the saturation of the image data IMGD will not be adjusted.

The image optimization processor 130 is coupled to the brightness compensator 120 . The image optimization processor 130 generates a saturation adjustment weight W_sat according to the brightness adjustment value dY of the image data. The image optimization processor 130 adjusts the brightness of the first image data IMG1 according to the calculated saturation adjustment weight W_sat to generate the output image data IMGO. Among them, the saturation can be calculated by the following formula (2):

Among them, Max represents the operation of taking the maximum value of the value in the corresponding brackets, and Min is the operation of taking the minimum value of the value in the corresponding brackets.

Please refer to FIG. 1 and FIG. 2 , wherein FIG. 2 shows a graph of a saturation adjustment weight function according to an embodiment of the present invention. The aforementioned saturation adjustment weight W_sat can be obtained by the saturation adjustment weight function shown in FIG. 2 . In FIG. 2, the curve 210 represents the relationship curve between the image brightness and the saturation adjustment weight W_sat when the data brightness adjustment value dY is greater than 0; the curve 220 represents the relationship between the image brightness and the saturation adjustment weight W_sat when the data brightness adjustment value dY is equal to 0 The relationship curve; and the curve 230 represents the relationship curve between the image brightness and the saturation adjustment weight W_sat when the data brightness adjustment value dY is less than 0. The curves 210 - 230 all converge toward the position where the saturation adjustment weight W_sat is equal to 1 along with the brightness of the image. That is to say, when the saturation adjustment weight W_sat is greater than 1, the saturation of the image data IMGD will be enhanced; when the saturation adjustment weight W_sat is equal to 1, the saturation of the image data IMGD remains unchanged; when the saturation adjustment weight W_sat is less than When 1, the saturation of the image data IMGD will be reduced. The saturation adjustment weight W_sat is inversely proportional to the brightness adjustment value of the image data IMGD.

The image optimization processor 130 may calculate the saturation adjustment weight W_sat by means of arithmetic operations according to formula (2). Of course, the relationship between the saturation adjustment weight W_sat and the brightness in the curves 210-230 in FIG. 2 can also be recorded in one or more look-up tables. The image optimization processor 130 can also find out the saturation adjustment weight W_sat through this lookup table.

On the other hand, the method of calculating the image data IMGO according to the saturation adjustment weight W_sat can be completed by the following relational expression (3) between the output image data IMGO and the saturation adjustment weight W_sat:

$\mathrm{<span\; class="notranslate">\; R</span>}\mathrm{<span\; class="notranslate">\; o</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; W</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; R</span>}\mathrm{<span\; class="notranslate">\; I</span>}\mathrm{<span\; class="notranslate">\; N</span>}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; *</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; W</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; G</span>}\mathrm{<span\; class="notranslate">\; I</span>}\mathrm{<span\; class="notranslate">\; N</span>}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; B</span>}\mathrm{<span\; class="notranslate">\; I</span>}\mathrm{<span\; class="notranslate">\; N</span>}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

$\mathrm{<span\; class="notranslate">\; G</span>}\mathrm{<span\; class="notranslate">\; o</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; W</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; G</span>}\mathrm{<span\; class="notranslate">\; I</span>}\mathrm{<span\; class="notranslate">\; N</span>}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; *</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; W</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; R</span>}\mathrm{<span\; class="notranslate">\; I</span>}\mathrm{<span\; class="notranslate">\; N</span>}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; B</span>}\mathrm{<span\; class="notranslate">\; I</span>}\mathrm{<span\; class="notranslate">\; N</span>}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

$\mathrm{<span\; class="notranslate">\; B</span>}\mathrm{<span\; class="notranslate">\; o</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; W</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; B</span>}\mathrm{<span\; class="notranslate">\; I</span>}\mathrm{<span\; class="notranslate">\; N</span>}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; *</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; W</span>}<span\; class="notranslate">\; \_</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; G</span>}\mathrm{<span\; class="notranslate">\; I</span>}\mathrm{<span\; class="notranslate">\; N</span>}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; R</span>}\mathrm{<span\; class="notranslate">\; I</span>}\mathrm{<span\; class="notranslate">\; N</span>}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

Wherein, RO, GO and BO are the image data of the three colors included in the output image data IMGO. Of course, the image optimization processor 130 can directly perform the arithmetic operation of the formula (3) to obtain the output image data IMGO, or the image optimization processor 130 can also create and record the output image data IMGO and the first image data IMG1 according to the formula (3). and a lookup table of the saturation adjustment weight W_sat, and adjust the weight W_sat according to the saturation according to the established lookup table to generate output image data IMGO.

On the other hand, the image optimization processor 130 may perform further adjustment actions on the output image data IMGO. Wherein, the image optimization processor 130 also calculates the brightness increment dY2 between the output image data IMGO and the first image data IMG1, and the image optimization processor 130 also calculates the detail variation of the output image data IMGO. The image optimization processor 130 then generates the adjusted output image data according to the brightness increase dY2 and the detail variation.

It should be noted that the brightness increase dY2 can be obtained by calculating the brightness difference between the output image data IMGO and the first image data IMG1 by the image optimization processor 130 . The degree of detail variation can be obtained by calculating the image optimization processor 130 for a plurality of pixel data included in the output image data IMGO. Wherein, the image optimization processor 130 may calculate the difference between the brightness values of each pixel data and adjacent pixel data adjacent to each pixel data to obtain detail variation.

Please refer to FIG. 1 , FIG. 3 and FIG. 4 , wherein FIG. 3 is a schematic diagram of a brightness increase weight function according to an embodiment of the present invention, and FIG. 4 is a schematic diagram of a detail variation weight function according to an embodiment of the present invention. The curve 310 shown in FIG. 3 represents the relation curve between the brightness increase and the brightness increase weight presented by the brightness increase weight function of the embodiment of the present invention, wherein the brightness increase and the brightness increase weight displayed by the curve 310 are inversely proportional. The image optimization processor 130 can calculate the brightness increase weight according to the calculated brightness increase dY2 through the curve 310 . In the illustration of FIG. 4 , the curve 410 represents the relationship curve between the degree of detail variation and the weight of detail variation presented by the detail variation weight function of the embodiment of the present invention, wherein the degree of detail variation and the weight of detail variation shown in the curve 410 are is proportional to , and when the detail variation is too large, the detail variation weight will tend to a stable value.

In addition, the image optimization processor 130 adds the obtained detail variation weights and brightness enhancement weights to generate detail correction weights, and adjusts the output image data IMGO through the detail correction weights to generate adjusted output image data IMGTO.

The image optimization processor 130 can adjust the generation of the output image data IMGTO according to the formula (4), and the formula (4) is as follows:

RTO＝RO+dY2×EDW

GTO＝GO+dY2×EDW

BTO＝BO+dY2×EDW (4)

Wherein, RTO, GTO and BTO are the image data of the three color lights included in the output image data IMGTO, and EDW is the detail correction weight.

Please refer to FIG. 5 below. FIG. 5 is a flow chart of an image optimization method according to an embodiment of the present invention. The steps of the image optimization method include: in step S510, receiving image data and ambient light brightness, and generating a backlight brightness adjustment value according to the image data and ambient light brightness; then, in step S520, generating image data according to the backlight brightness adjustment value brightness adjustment value, and adjust the brightness of the image data according to the brightness adjustment value of the image data to generate the first image data; finally, in step S530, generate a saturation adjustment weight according to the brightness adjustment value of the image data, and adjust the weight according to the saturation to adjust the brightness of the first image data to generate output image data.

The details of the operation of this embodiment have been described in detail in the foregoing embodiments and implementations, and will not be described in detail below.

To sum up, the present invention not only adjusts the brightness of the image data according to the brightness adjustment value of the backlight, but also adjusts the image data taking into account the saturation of the image. In this way, in addition to controlling the brightness of the backlight module to save power, the display device also takes into account the quality of image display, effectively achieving the effect of saving and affecting optimization.

Claims (13)

1. an image display device, including:

One analysis of image content device, receives a view data and an environmental light brightness, according to this picture number According to this and this environmental light brightness produces a backlight illumination adjusted value；

One luminance compensation device, couples this analysis of image content device, produces according to this backlight illumination adjusted value One image data illumination adjusted value and an image data illumination adjust ratio, and bright according to this view data Degree adjusted value and this image data illumination adjust ratio and adjust the brightness of this view data to produce one first View data；And

One image optimization processor, couples this luminance compensation device, comes according to this image data illumination adjusted value Producing a saturation and adjust weight, this image optimization processor also adjusts according to this saturation adjustment weight The brightness of this first view data is to produce an output view data.

2. image display device as claimed in claim 1, wherein this image optimization processor also calculates this A brightness amplification between output view data and this first view data, and calculate this output view data One details degree of variation, this image optimization processor and adjusting according to this brightness amplification and this details degree of variation This output view data whole is to export view data after producing an adjustment.

3. image display device as claimed in claim 2, wherein to calculate this defeated for this image optimization processor Go out the view data luminance difference with this first view data to obtain this brightness amplification.

4. image display device as claimed in claim 2, wherein this output view data includes multiple picture Prime number evidence, this image optimization processor calculates multiple neighbours that respectively this pixel data is neighbouring with respectively this pixel data The difference of the brightness value of nearly pixel data obtains this details degree of variation.

5. image display device as claimed in claim 2, wherein this image optimization processor is bright according to this Degree amplification and a brightness amplification weighting function obtain a brightness correction weighted value, and this image optimization processes Device also obtains a details variation correction weight according to this details degree of variation and details variation weighting function Value.

6. image display device as claimed in claim 5, wherein this image optimization processor is bright according to this Degree revise weighted value and this details variation revise weighted value and obtain a details correction weight, this figure As optimized processor and according to this details correction weight adjust this output view data to produce this adjustment after Output view data.

7. image display device as claimed in claim 1, wherein this image optimization processor is satisfied according to one Adjust weighting function and this image data illumination adjusted value with degree to produce this saturation and adjust weight, wherein, This saturation adjusts weight and is inversely proportional to this image data illumination adjusted value.

8. an image optimization method, it is adaptable to image display device, including:

Receive a view data and an environmental light brightness, according to this view data and this environmental light brightness Produce a backlight illumination adjusted value；

Produce an image data illumination adjusted value according to this backlight illumination adjusted value and a view data is bright Degree adjustment ratio, and adjust according to this image data illumination adjusted value and this image data illumination adjustment ratio The brightness of this view data whole is to produce one first view data；And

Produce a saturation according to this image data illumination adjusted value and adjust weight, and according to this saturation Adjust weight and adjust the brightness of this first view data to produce an output view data.

9. image optimization method as claimed in claim 8, the most also includes:

Calculate the brightness amplification between this output view data and this view data；

Calculate a details degree of variation of this output view data；And

This output view data is adjusted to produce an adjustment according to this brightness amplification and this details degree of variation Rear output view data.

10. image optimization method as claimed in claim 9, the most also includes:

Calculate this output view data luminance difference with this view data to obtain this brightness amplification.

11. image optimization methods as claimed in claim 9, wherein, this output view data includes multiple Pixel data, this image optimization method also includes:

Calculate respectively this pixel data and the brightness value of the multiple neighborhood pixels data neighbouring with respectively this pixel data Difference obtain this details degree of variation.

12. image optimization methods as claimed in claim 9, wherein, adjust weight according to this saturation and come The brightness adjusting this first view data includes with the step producing this output view data:

A brightness correction weighted value is obtained according to this brightness amplification and a brightness amplification weighting function；

Obtain a details variation according to this details degree of variation and details variation weighting function and revise weight Value；And

Make a variation according to this brightness correction weighted value and this details that revise weighted value and adjust this output figure As data are to export view data after producing this adjustment.

13. image optimization methods as claimed in claim 8, wherein, adjust according to this image data illumination Value produces the step of this saturation adjustment weight and includes:

Adjust weighting function according to a saturation and this image data illumination adjusted value produces this saturation and adjusts Whole weight,

Wherein, this saturation adjustment weight is inversely proportional to this image data illumination adjusted value.