CN101656852B - Image processing device and image processing method - Google Patents
Image processing device and image processing method Download PDFInfo
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- CN101656852B CN101656852B CN2008102110890A CN200810211089A CN101656852B CN 101656852 B CN101656852 B CN 101656852B CN 2008102110890 A CN2008102110890 A CN 2008102110890A CN 200810211089 A CN200810211089 A CN 200810211089A CN 101656852 B CN101656852 B CN 101656852B
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Abstract
The invention discloses an image processing device and an image processing method for regulating the contrast of an input image. The input image consists of a plurality of pixels and each pixel is provided with an other input luminance. The image processing device can carry out normalization processing on the input luminance of each pixel so as to acquire an other normalization luminance of each pixel. Moreover, the image processing device generates luminance statistic data according to the pixels and determines a plurality of critical luminances according to the luminance statistic data. According to the normalization luminances and the critical luminances, the image processing device can dynamically change luminance gain values of specified areas in the input image, thereby regulating the contrast of the input image.
Description
Technical field
The present invention relates to a kind of image processor and image treatment method, particularly relate to a kind of in order to adjust the device and method of the contrast of importing image.
Background technology
Generally speaking, the contrast of image is meant the brightness ratio in clear zone and dark space in the image.The enhancing of contrast can make part bright relatively in the image brighter again, and dark relatively part is dark again.Strengthen contrast and make image distortion slightly sometimes, but, suitably strengthen contrast and can obtain more exhilarating image most of people.
For display or TV, the enhancing of contrast can be realized by the relation that changes GTG signal and brightness by the Gamma coefficient adjustment on the one hand; The gain that can be changed the image brilliance component by the chip (for example video decoded device or set-top box) of display is adjusted on the other hand.Yet one group of fixing contrast is set and is not suitable for various images usually.
See also Fig. 1.Fig. 1 shows an image by a known contrast adjustment brightness output curve diagram that mode produced.Trunnion axis is represented the brightness imported, and vertical axis is represented the brightness of exporting.Solid line represent the brightness curve of output dotted line that is left intact represent through the contrast adjusted brightness curve of output.As shown in Figure 1, after adjusting, brightness originally is lowered less than the brightness meeting of the pixel of 130 GTGs; And brightness originally is enhanced greater than the brightness meeting of the pixel of 130 GTGs, by this to strengthen the contrast of image.
Implementation for adjusted brightness curve of output can realize by following formula:
L
out＝L
in*G；
Wherein, L
OutWith L
InBe represented as the output and input brightness of each pixel in the image respectively.G is a yield value, and scope is between 0～2.The input brightness L that varies in size
InCorresponding different yield value G, promptly yield value G is input brightness L
InFunction.Input brightness L
InCan build on one group of table of comparisons with the relation of yield value G.When circuit is realized, can be according to input brightness L
InFind out behind the pairing yield value G by the table of comparisons and can produce output brightness at the formula of execution following formula.
Yet only can the highlight contrast of the wider image of branch of mode is adjusted in known contrast.If the brightness of some image only is distributed between 0～130 GTG, after the above-mentioned processing of process, not only contrast does not increase, and overall image brightness meeting reduces on the contrary, makes the part of image low-light level too secretly lose details, causes deleterious; Conversely speaking, if the brightness of some image only is distributed between 130～255 GTGs, similarly pass through above-mentioned processing after, just the brightness of overall image promotes, but contrast does not strengthen.As known from the above, known contrast is adjusted mode and is not suitable for various image.
Therefore, main category of the present invention is to provide a kind of image processor and image treatment method, to address the above problem.
Summary of the invention
A category of the present invention is to provide a kind of image processor and image treatment method thereof, in order to adjust the contrast of an input image.The input image is made up of a plurality of pixel and each pixel has other input brightness.
According to a specific embodiment of the present invention, image processor comprises first processing module, second processing module, gain decision module and the 3rd processing module.The gain decision module is coupled respectively to first processing module and second processing module.The 3rd processing module is coupled respectively to second processing module and gain decision module.
First processing module is handled (normalization procedure) in order to a normalization is carried out in the input brightness of these a plurality of pixels, and then obtains other normalization brightness of each pixel.First processing module and in order to one first yield value according to the brightness of normalization brightness and one first yield value function decision corresponding specification.Second processing module is in order to adding up the input brightness of these a plurality of pixels producing a luminance statistic data, and determines a plurality of critical luminances (threshold lightness) according to luminance statistic data.Second processing module and in order to determine one second yield value of corresponding described critical luminance according to described critical luminance and one second yield value function.
The gain decision module is in order to determine a target second yield value of corresponding specification brightness in described second yield value according to pairing first yield value of the normalization brightness of each pixel.The 3rd processing module produces one of corresponding input brightness according to this input brightness of each pixel, pairing first yield value and pairing target second yield value and exports brightness, and the contrast of importing image by this is adjusted.
Another specific embodiment according to the present invention is a kind of image treatment method.One input image is made up of a plurality of pixel and each pixel has other input brightness.
This method is carried out a normalization to the input brightness of these a plurality of pixels and is handled, and then obtains other normalization brightness of each pixel.This method and the input brightness of these a plurality of pixels added up producing a luminance statistic data, and determine a plurality of critical luminances according to luminance statistic data.
Secondly, according to normalization brightness and one first yield value function, one first yield value of this method decision corresponding specification brightness.According to described critical luminance and one second yield value function, this method determines one second yield value of corresponding described critical luminance.
Then, according to pairing first yield value of the normalization brightness of each pixel, this method determines a target second yield value of corresponding specification brightness in described second yield value.
Afterwards, according to the input brightness of each pixel, pairing first yield value and pairing target second yield value, this method produces an output brightness of corresponding input brightness, and the contrast of importing image by this is adjusted.
Can be further understood by the following detailed description and accompanying drawings about the advantages and spirit of the present invention.
Description of drawings
Fig. 1 shows an image by the known contrast adjustment brightness output curve diagram that mode produced.
Fig. 2 A and Fig. 2 B show the function block diagram according to image processor of the present invention.
Fig. 3 A shows its interior schematic diagram that stores first table of comparisons of first storage element.
Fig. 3 B shows its interior schematic diagram that stores second table of comparisons of second storage element.
Fig. 4 shows the schematic diagram that luminance statistic data is expressed as a brightness statistics distribution map.
Fig. 5 A and Fig. 6 A show the brightness statistics histogram of the image of two kinds of needs adjustment contrasts respectively.
Fig. 5 B and Fig. 6 B show the brightness curve analog result through image processor adjustment of the present invention image gained later respectively.
Fig. 7 shows the flow chart according to the image treatment method of another specific embodiment of the present invention.
The reference numeral explanation
1: image processor
12: the second processing modules of 10: the first processing modules
14: 16: the three processing modules of gain decision module
20: the second storage elements of 18: the first storage elements
24: the second transducers of 22: the first transducers
164: the second multipliers
200: the second tables of comparisons of 180: the first tables of comparisons
Iin: input image Iout: image output
Lin: input brightness Lout: output brightness
LN: normalization brightness LL: critical dark space brightness
LH: critical clear zone brightness GBL: dark space luminance gain value
GBH: clear zone luminance gain value
S100～S110: process step
Embodiment
See also Fig. 2 A.Fig. 2 A shows the functional block diagram according to the image processor 1 of a specific embodiment of the present invention.Image processor 1 of the present invention is in order to the brightness of adjustment input image Iin, and then the contrast of improvement input image Iin.In general, input image Iin is made up of a plurality of pixel, and each pixel has other input brightness.
Shown in Fig. 2 A, image processor 1 comprises first transducer 22, second transducer 24, first processing module 10, second processing module 12, the 3rd processing module 16, gain decision module 14, first storage element 18 and second storage element 20.Gain decision module 14 is coupled respectively to first processing module 10 and second processing module 12.The 3rd processing module 16 is coupled respectively to second processing module 12 and gain decision module 14.First transducer 22 is coupled respectively to first processing module 10, second processing module 12 and the 3rd processing module 16.Second transducer 24 is coupled respectively to first transducer 22 and the 3rd processing module 16.First storage element 18 is coupled to first processing module 10, and second storage element 20 is coupled to second processing module 12.
In this embodiment, input image Iin meets first color space, for example rgb color space.First transducer 22 is converted to second color space of brightness and color-separated in order to will import image Iin by rgb color space, and first transducer 22 can transmit the Lin to the first of an input brightness else processing module 10, second processing module 12 and the 3rd processing module 16 of each pixel by this.In practical application, second color space can be YCbCr, Yuv, YIQ, CIELab or Luv color space.
L wherein
NorRepresentative normalization brightness, Lin representative input brightness, L
MinRepresent a minimum brightness of image, L
MaxRepresent a high-high brightness of image.
Generally speaking, the pixel of digitized video is to store with 8, so the lightness distribution of each pixel is 0～255 GTG, just 256 GTGs.Yet, the brightness of natural image all be not equably branch in 256 GTGs.For example, the brightness than the shadow picture may be distributed in 150 below the GTG mostly.The advantage that normalization of the present invention is handled is and the brightness of whole image can be redistributed, and its distribution can broadlyer be handled so that carry out follow-up contrast.Because therefore 255 maximum gray values that GTG is 8 images handle the normalization brightness L of back gained through standardizing
NorDistribution be 0～255 GTG.
Receive the input brightness Lin of these a plurality of pixels when second processing module 12 after, second processing module 12 is added up producing a luminance statistic data (lightness statistics) in order to the input brightness Lin to described pixel, and determines a plurality of critical luminances according to luminance statistic data.Second processing module 12 and in order to according to described critical luminance and one second yield value function decision a plurality of second yield values of corresponding described critical luminance respectively.
In a specific embodiment, shown in Fig. 2 A, second storage element, 20 its interior one second tables of comparisons 200 that store.A plurality of critical luminances and a plurality of second yield value that second table of comparisons, 200 records are produced according to this second yield value function, wherein each described critical luminance corresponds respectively to the one in described second yield value.By this, second processing module 12 can be searched second table of comparisons 200 with a plurality of second yield values of taking out corresponding described critical luminance respectively and export gain decision module 14 to.
Below will be by an example to further describe conception of the present invention.In this example, second processing module 12 can determine critical dark space (dark-area) brightness and critical clear zone (bright-area) brightness according to luminance statistic data.As shown in Figure 4, luminance statistic data can be expressed as a brightness statistics distribution map.The brightness value of transverse axis remarked pixel, and the longitudinal axis is represented the pairing number of pixels of each brightness value.
In a specific embodiment, the brightness of critical dark space is by in the statistical Butut, GTG by minimum begins the incremental calculation area, when the ratio of the area up between the GTG of minimum and a specific GTG and the gross area of statistical Butut arrives one first critical value (for example 3%), this specific GTG is promptly as the brightness of critical dark space; And the brightness of critical clear zone is by in the statistical Butut, GTG by maximum begins the reference area that successively decreases, when the ratio of the gross area of the GTG of maximum and area between another specific GTG and statistical Butut arrives one second critical value (for example 3%), this specific GTG is promptly as the brightness of critical clear zone.Be noted that first critical value and second critical value design according to the actual requirements.The quantity of pixel dark in the image is represented in the brightness of critical dark space, and pixel dark in the big more expression image of critical dark space brightness is few more; Otherwise the quantity of pixel bright in the image is represented in the brightness of critical clear zone, and pixel bright in the big more expression image of critical clear zone brightness is many more.
In addition, shown in Fig. 3 B, second table of comparisons 200 writes down a plurality of critical dark space brightness LL, a plurality of critical clear zone brightness LH, a plurality of dark space luminance gain value GBL and a plurality of clear zone luminance gain value GBH in advance, wherein each this critical dark space brightness LL is corresponding to the one among the described dark space luminance gain value GBL, and each this critical clear zone brightness LH is corresponding to the one among the described clear zone luminance gain value GBH.By this, second processing module 12 can be searched second table of comparisons 200 to take out corresponding respectively critical dark space brightness LL that is calculated and dark space luminance gain value GBL and the clear zone luminance gain value GBH of critical clear zone brightness LH.
In this embodiment, the scope of the first yield value GA can be between-1～1.Accept the function that above-mentioned example illustrates gain decision module 14, when the received first yield value GA of gain decision module 14 more than or equal to 0 the time, gain decision module 14 output clear zone luminance gain value GBH to the three processing modules 16; When the received first yield value GA of gain decision module 14 less than 0,14 output of gain decision module dark space luminance gain value GBL.
The 3rd processing module 16 produces a corresponding output brightness Lout who imports brightness Lin according to the input brightness Lin of each pixel, the pairing first yield value GA and pairing target second yield value, and the contrast of importing image Iin by this is adjusted.
See also Fig. 2 B.In a specific embodiment, the 3rd processing module 16 comprises first multiplier 160, adder 162 and second multiplier 164.First multiplier 160 is coupled to second processing module 12 and gain decision module 14, and adder 162 is coupled to first multiplier 160 and second multiplier 164.In addition, in order to help understand conception of the present invention, the input brightness Lin of each pixel can be adjusted by following arithmetic expression among the input image Iin:
G(i)＝1+A(i)*B(j)；
Wherein A (i) represents first yield value, and B (j) represents target second yield value, and A (i) * B (j) represents the 3rd yield value, and G (i) represents the 4th yield value.The scope of A (i) is between-1～1; The scope of B (j) is between 0～1; The scope of G (i) is between 0～2.Be noted that the scope of A (i), B (j) and G (i) designs according to the actual requirements, does not exceed with above-mentioned scope.
After second multiplier 164 produces output brightness Lout, second transducer 24 will be imported image Iin and be converted to first color space (for example rgb color space) by second color space (for example Lab color space) and image output Iout is exported.
Can find out that by above arithmetic expression if the size of the target second yield value B (j) changes, the 4th last yield value G (i) also changes.Thus, can dynamically adjust the size of the 4th yield value G (i), to strengthen various contrasts by the content of input image Iin according to image processor 1 of the present invention with image of different Luminance Distribution.
The example that below will lift two kinds of contrasts of adjusting image by different way is to highlight the advantage of image processor 1 of the present invention.See also Fig. 5 A and Fig. 6 A.Fig. 5 A and Fig. 6 A show the brightness statistics histogram of the image of two kinds of needs adjustment contrasts respectively.With Fig. 5 A is example, desires suitably to strengthen the contrast of image, needs the part (for example 130～255 GTG between) at high brightness significantly to improve brightness, and reduces brightness a little in the part of low-light level (for example 0～130 GTG between).In order to adjust contrast according to this kind mode, gain decision module 14 can output valve be that 0.5 clear zone luminance gain value and value are 0.2 dark space luminance gain value.With Fig. 6 A is example, desires suitably to strengthen the contrast of image, needs to improve brightness a little in the part of high brightness, and significantly reduces brightness in the part of low-light level.
See also Fig. 5 B and Fig. 6 B.Fig. 5 B and Fig. 6 B show the image of Fig. 5 A and Fig. 6 A representative respectively and adjust the brightness curve analog result of gained later through image processor 1 of the present invention.Shown in Fig. 5 B, after adjusting, the brightness of hi-lite improves more yield value really; Otherwise shown in Fig. 6 B, the brightness of low-light level part significantly reduces really.The analog result of Fig. 5 B and Fig. 6 B confirms that image processor 1 of the present invention can be dynamically and flexibly adjust the contrast of image.
See also Fig. 7.Fig. 7 shows the flow chart according to the image treatment method of another specific embodiment of the present invention.One input image is made up of a plurality of pixel and each pixel has other input brightness.
In step S100, this method is carried out a normalization to the input brightness of these a plurality of pixels and is handled, and then obtains other normalization brightness of each pixel.
In step S102, this method and the input brightness of these a plurality of pixels added up producing a luminance statistic data, and determine a plurality of critical luminances according to luminance statistic data.The generating routine of normalization brightness and a plurality of critical luminances as before instruction, do not repeat them here.
Behind step S100, this method execution in step S104, according to normalization brightness and one first yield value function, one first yield value of this method decision corresponding specification brightness.In a specific embodiment, step S104 can utilize comparison list to carry out.The table of comparisons can write down a plurality of normalization brightness that produced according to the first yield value function and the table of comparisons of a plurality of first yield values in advance, and wherein each described normalization brightness corresponds respectively to the one in described first yield value.
Behind step S102, this method execution in step S106, according to described critical luminance and one second yield value function, this method decision is a plurality of second yield values of corresponding described critical luminance respectively.In a specific embodiment, step S106 can utilize comparison list to carry out.The table of comparisons can write down a plurality of critical luminances and a plurality of second yield value that is produced according to the second yield value function in advance, and wherein each described critical luminance corresponds respectively to the one in described second yield value.
After determining first yield value and described second yield value, this method execution in step S108, according to pairing first yield value of the normalization brightness of each pixel, this method determines a target second yield value of corresponding specification brightness in described second yield value.
Afterwards, this method execution in step S110, according to the input brightness of each pixel, pairing first yield value and pairing target second yield value, this method produces an output brightness of corresponding input brightness, and the contrast of importing image by this is adjusted.
In a specific embodiment, step S110 can realize by the following step.At first, first yield value be multiply by target second yield value to produce one the 3rd yield value.Then, the 3rd yield value and a preset value are produced one the 4th yield value mutually.Afterwards, the 4th yield value is multiply by in the input brightness of each pixel, to produce output brightness corresponding to this input brightness.
Compared to prior art, import the brightness of image according to image processor of the present invention and image treatment method by adjustment, and then improve the contrast of input image.Especially, the present invention can dynamically choose suitable yield value respectively to adjust its brightness respectively at the part of high brightness and the part of low-light level in the input image.By this, even the uneven image of Luminance Distribution still can obtain the appropriate brightness adjustment so that the contrast of image is improved, and then the quality of promoting image.
By the above detailed description of preferred embodiments, be to wish to know more to describe feature of the present invention and spirit, and be not to come category of the present invention is limited with the above-mentioned preferred embodiment that is disclosed.On the contrary, its objective is that hope can contain in the category of claim of being arranged in of various changes and tool equality institute of the present invention desire application.Therefore, claim of the present invention should be done the broadest explanation according to above-mentioned explanation, contains the arrangement of all possible change and tool equality to cause it.
Claims (17)
1. image processor, in order to adjust a contrast of an input image, this input image is made up of a plurality of pixel and each pixel has one and else imports brightness, and this image processor comprises:
One first processing module, this first processing module is handled in order to a normalization is carried out in the input brightness of these a plurality of pixels, and then obtain one of each pixel other normalization brightness, this first processing module and in order to determine one first yield value according to this normalization brightness and one first yield value function to the brightness of should standardizing;
One second processing module, this second processing module is in order to add up to produce a luminance statistic data the input brightness of these a plurality of pixels, and determine a plurality of critical luminances according to this luminance statistic data, this second processing module and in order to determine one second yield value of corresponding described critical luminance according to described critical luminance and one second yield value function;
One gain decision module, this gain decision module is coupled respectively to this first processing module and this second processing module, and this gain decision module is in order to determine a target second yield value to the brightness of should standardizing in described second yield value according to pairing this first yield value of this normalization brightness of each pixel; And
One the 3rd processing module, the 3rd processing module is coupled respectively to this second processing module and this gain decision module, the 3rd processing module produces importing an output brightness of brightness according to this input brightness of each pixel, pairing this first yield value and pairing this target second yield value, and this contrast of this input image is adjusted by this.
2. image processor as claimed in claim 1, wherein the 3rd processing module comprises:
One first multiplier, this first multiplier is in order to multiply by this first yield value this target second yield value to produce one the 3rd yield value;
One adder, this adder are coupled to this first multiplier, and this adder is in order to be produced one the 4th yield value mutually with the 3rd yield value and a preset value; And
One second multiplier, this second multiplier is coupled to this adder, and this second multiplier multiply by the 4th yield value to produce importing this output brightness of brightness in order to will import brightness.
3. image processor as claimed in claim 1 further comprises:
One storage element, this storage element is coupled to this first processing module, its interior comparison list that stores of this storage element, a plurality of normalization brightness and a plurality of first yield value that this table of comparisons record is produced according to this first yield value function, each described normalization brightness corresponds respectively to the one in described a plurality of first yield value.
4. image processor as claimed in claim 1 further comprises:
One storage element, this storage element is coupled to this second processing module, its interior comparison list that stores of this storage element, a plurality of critical luminances and a plurality of second yield value that this table of comparisons record is produced according to this second yield value function, each described critical luminance corresponds respectively to the one in described a plurality of second yield value.
5. image processor as claimed in claim 4, wherein these a plurality of critical luminances comprise critical dark space brightness and a critical clear zone brightness, described second yield value comprises a plurality of dark spaces luminance gain value and a plurality of clear zones luminance gain value, this critical dark space brightness is corresponding to the dark space luminance gain value in the luminance gain value of described a plurality of dark spaces, and this critical clear zone brightness is corresponding to the clear zone luminance gain value in the luminance gain value of described a plurality of clear zones.
6. image processor as claimed in claim 1, wherein this normalization is handled and is calculated described normalization brightness by following formula:
L wherein
NorRepresent this normalization brightness, L
InRepresent this input brightness, L
MinRepresent a minimum brightness of this image, L
MaxRepresent a high-high brightness of this image.
7. image processor as claimed in claim 1, further comprise one first transducer, this first transducer is coupled respectively to this first processing module, this second processing module and the 3rd processing module, this image meets one first color space, and this first transducer is in order to be converted to one second color space with this image by this first color space.
8. image processor as claimed in claim 7, further comprise one second transducer, this second transducer is coupled respectively to this first transducer and the 3rd processing module, and this second transducer is in order to be converted to this first color space with this image by this second color space.
9. image processor as claimed in claim 8, wherein this first color space is a rgb color space, and this second color space is selected from the one in the group that is made up of YCbCr, Yuv, YIQ, CIELab and Luv color space.
10. image treatment method, in order to adjust a contrast of an input image, this input image is made up of a plurality of pixel and each pixel has one and else imports brightness, and this method comprises the following step:
(a) normalization is carried out in the input brightness of these a plurality of pixels and handled, and then obtain other normalization brightness of each pixel;
(b) according to this normalization brightness and one first yield value function, decision is to one first yield value of the brightness of should standardizing;
(c) the input brightness of these a plurality of pixels is added up producing a luminance statistic data, and determined a plurality of critical luminances according to this luminance statistic data;
(d), determine one second yield value of corresponding described critical luminance according to described critical luminance and one second yield value function;
(e) according to pairing this first yield value of this normalization brightness of each pixel, decision is to a target second yield value of the brightness of should standardizing in described second yield value; And
(f) according to this input brightness, pairing this first yield value and pairing this target second yield value of each pixel, produce importing an output brightness of brightness, this contrast of this input image is adjusted by this.
11. method as claimed in claim 10, wherein step (f) is performed by the following step:
(f1) this first yield value be multiply by this target second yield value to produce one the 3rd yield value;
(f2) the 3rd yield value and a preset value are produced one the 4th yield value mutually; And
(f3) should import brightness and multiply by the 4th yield value, to produce this output brightness corresponding to this input brightness.
12. method as claimed in claim 10, wherein step (b) utilizes comparison list to carry out, the a plurality of normalization brightness that this table of comparisons record is produced according to this first yield value function and the table of comparisons of a plurality of first yield values, each described normalization brightness corresponds respectively to the one in described a plurality of first yield value.
13. method as claimed in claim 10, wherein step (d) utilizes comparison list to carry out, a plurality of critical luminances and a plurality of second yield value that this table of comparisons record is produced according to this second yield value function, each described critical luminance corresponds respectively to the one in described a plurality of second yield value.
14. method as claimed in claim 13, wherein these a plurality of critical luminances comprise critical dark space brightness and a critical clear zone brightness, described second yield value comprises a plurality of dark spaces luminance gain value and a plurality of clear zones luminance gain value, this critical dark space brightness is corresponding to the dark space luminance gain value in the luminance gain value of described a plurality of dark spaces, and this critical clear zone brightness is corresponding to the clear zone luminance gain value in the luminance gain value of described a plurality of clear zones.
15. method as claimed in claim 10, wherein this normalization is handled and is calculated described normalization brightness by following formula:
L wherein
NorRepresent this normalization brightness, L
InRepresent this input brightness, L
MinRepresent a minimum brightness of this image, L
MaxRepresent a high-high brightness of this image.
16. method as claimed in claim 10, this image meet one first color space, this method further comprises the following step:
In step (a) before, this image is converted to one second color space by this first color space; And
In step (f) afterwards, this image is converted to this first color space by this second color space.
17. method as claimed in claim 16, wherein this first color space is a rgb color space, and this second color space is selected from the one in the group that is made up of YCbCr, Yuv, YIQ, CIELab and Luv color space.
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| CN1655015A (en) * | 2004-02-13 | 2005-08-17 | 钰瀚科技股份有限公司 | Luminance compensation method and device for liquid crystal display |
| CN1956495A (en) * | 2005-10-27 | 2007-05-02 | 帆宣系统科技股份有限公司 | Method for image dynamic contrast stretch and its device |
| CN101072363A (en) * | 2006-05-10 | 2007-11-14 | 广达电脑股份有限公司 | Image processing device and method |
| JP2008118608A (en) * | 2006-10-11 | 2008-05-22 | Victor Co Of Japan Ltd | Video signal processor and video display device |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1655015A (en) * | 2004-02-13 | 2005-08-17 | 钰瀚科技股份有限公司 | Luminance compensation method and device for liquid crystal display |
| CN1956495A (en) * | 2005-10-27 | 2007-05-02 | 帆宣系统科技股份有限公司 | Method for image dynamic contrast stretch and its device |
| CN101072363A (en) * | 2006-05-10 | 2007-11-14 | 广达电脑股份有限公司 | Image processing device and method |
| JP2008118608A (en) * | 2006-10-11 | 2008-05-22 | Victor Co Of Japan Ltd | Video signal processor and video display device |
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