Graphics blending for high dynamic range video
US-9584786-B2 · Feb 28, 2017 · US
US9961237B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9961237-B2 |
| Application number | US-201615544320-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jan 14, 2016 |
| Priority date | Jan 19, 2015 |
| Publication date | May 1, 2018 |
| Grant date | May 1, 2018 |
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A display management processor receives an input image with enhanced dynamic range to be displayed on a target display which has a different dynamic range than a reference display. The input image is first transformed into a perceptually-quantized (PQ) color space, preferably the IPT-PQ color space. A color volume mapping function, which includes an adaptive tone-mapping function and an adaptive gamut mapping function, generates a mapped image. A detail-preservation step is applied to the intensity component of the mapped image to generate a final mapped image with a filtered tone-mapped intensity image. The final mapped image is then translated back to the display's preferred color space. Examples of the adaptive tone mapping and gamut mapping functions are provided.
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The invention claimed is: 1. A method comprising: accessing an input image in a first color space with a first dynamic range; applying a color transformation step to the input image to determine a first output image in a perceptually-quantized IPT (IPT-PQ) color space, the first output image comprising intensity pixel values and chroma components pixel values, wherein the color transformation step comprises applying a non-linear perceptual quantizer function to a function of the input image; applying a color-volume mapping function to the first output image to generate a tone-mapped output image, the tone-mapped output image comprising intensity pixel values and chroma components pixel values, wherein the color-volume mapping function comprises a tone mapping function, a saturation mapping function, and a pixel saturation estimate function, wherein the tone mapping function generates the intensity pixel values of the tone-mapped output image by applying a non-linear mapping to the intensity pixel values of the first output image, wherein the saturation mapping function generates the chroma components pixel values of the tone-mapped output image by adjusting the chroma components pixel values of the first output image based on changes in intensity, wherein the pixel saturation estimate function computes a saturation metric (S) as the sum of squares of the chroma components pixel values of the first output image, wherein the saturation metric is applied to the tone-mapped output image to darken bright saturated colors and to desaturate highly saturated colors, thereby modifying the intensity pixel values and the chroma components pixel values; and applying a detail preservation function to the modified intensity pixel values of the tone-mapped output image to generate intensity pixel values of a filtered tone-mapped output image, the filtered tone-mapped output image comprising the modified chroma components pixel values of the tone-mapped output image. 2. The method of claim 1 , wherein applying the color transformation step further comprises: removing any non-linear encoding from the input image to generate a linear image; converting the linear image into an LMS color image; and applying the non-linear perceptual quantizer (PQ) function to the LMS color image to generate the first output image. 3. The method of claim 2 , wherein the non-linear perceptual quantizer function comprises the SMPTE ST 2084 mapping function. 4. The method of claim 1 , wherein the tone-mapping function is expressed as a parameterized sigmoidal tone curve function, wherein parameters of the function are determined based on characteristics of a source display and a target display. 5. The method of claim 4 , wherein the characteristics of the source display comprise a minimum brightness value and a maximum brightness value for the source display. 6. The method of claim 4 , wherein the characteristics of the target display comprise a minimum brightness value and a maximum brightness value for the target display. 7. The method of claim 4 , wherein the characteristics of the source display are accessed through received source display metadata. 8. The method of claim 4 , wherein the sigmoidal tone function is expressed as I m = ( C 1 + C 2 I o Slope 1 + C 3 I o Slope ) Rolloff wherein C 1 , C 2 , C 3 , Slope, and Rolloff are constants defining the parameters of the tone-mapping function, and for an input I o , represented by an intensity pixel value of the first output image, I m is a corresponding output value, represented by the corresponding intensity pixel value of the tone-mapped output image. 9. The method of claim 4 , wherein parameters of the tone-mapping function are further determined based on a Brightness value and a Contrast value to adjust overall brightness and contrast of the tone-mapped output image. 10. The method of claim 1 , wherein the saturation mapping function is expressed as ƒ SM ( I o )= I m −I o +1 wherein I m denotes the output of the tone-mapping function, and I o denotes the intensity pixel values of the first output image, and wherein applying the color-volume mapping function comprises computing: I m =ƒ T ( I o )*(1− S *α), P m =P*ƒ SM ( I o )*(1− S *β), T m =T*ƒ SM ( I o )*(1− S *β), where S denotes the saturation metric generated by the pixel saturation estimation function, α and β denote input weights, ƒ T (I o ) denotes the tone-mapping function, ƒ SM (I o ) denotes the saturation mapping function, I o denotes the intensity pixel values of the first output image, P and T denote the chroma components pixel values of the first output image, I m denotes the pixel values of the tone-mapped output image, and P m and T m denote the color components pixel values of the tone-mapped output image. 11. The method of claim 10 , wherein the values of (1−S*α) and (1−S*β) are clamped to always be larger than zero. 12. The method of claim 1 , wherein applying the detail preservation function further comprises computing: D=I o −I m , B=F ( D,H ), Ex=F ( B,Hx ), Ey=F ( B,Hy ), E =(| Ex|+|Ey| )* W MSE +(1− W MS ), I mƒ =I o −B−E *( D−B ) where F(D,H) denotes applying to image D a filter with kernel H, I o denotes intensity pixel values of the first output image, I m denotes the intensity pixel values of the tone-mapped output image, I mƒ denotes the intensity pixel values of the filtered tone-mapped output image, B denotes the output of a blur filter, Ex denotes the output of a horizontal edge-detection filter, Ey denotes the output of a vertical edge-detection filter, and W MSE and W MS are weights. 13. The method of claim 12 , wherein the E output value is further clamped to be between 0 and 1. 14. The method of claim 12 , wherein the kernel H comprises a 5×11 Gaussian filter with standard deviation equal to 2. 15. The method of claim 12 , wherein the kernel H comprises a low-pass filter. 16. An apparatus comprising a processor and configured to perform any one of the methods recited in claim 1 . 17. A non-transitory computer-readable storage medium having stored thereon computer-executable instruction for executing a method in accordance with claim 1 .
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