Optimizing high dynamic range images for particular displays
US-2019052908-A1 · Feb 14, 2019 · US
US10432977B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10432977-B2 |
| Application number | US-201615749231-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 3, 2016 |
| Priority date | Aug 4, 2015 |
| Publication date | Oct 1, 2019 |
| Grant date | Oct 1, 2019 |
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In a method to improve backwards compatibility when decoding high-dynamic range images coded in a wide color gamut (WCG) space which may not be compatible with legacy color spaces, hue and/or saturation values of images in an image database are computed for both a legacy color space (say, YCbCr-gamma) and a preferred WCG color space (say, IPT-PQ). Based on a cost function, a reshaped color space is computed so that the distance between the hue values in the legacy color space and rotated hue values in the preferred color space is minimized HDR images are coded in the reshaped color space. Legacy devices can still decode standard dynamic range images assuming they are coded in the legacy color space, while updated devices can use color reshaping information to decode HDR images in the preferred color space at full dynamic range.
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The invention claimed is: 1. A method to improve backward compatible decoding, the method comprising: accessing with a processor an image database; computing first hue values in a first color space of the images in the image database; computing second hue values in a second color space of the images in the database; computing a hue rotation angle by minimizing a hue cost function, wherein the hue cost function is based on a difference measure of the first hue values and rotated second hue values; generating based on the hue rotation angle a color-rotation matrix for color-rotating input images prior to encoding; computing first saturation values of the images in the database in the first color space; transforming the images in the database into the second color space to generate transformed images; applying the color-rotation matrix to the transformed images to generate color-rotated images; computing second saturation values of the color-rotated images; computing a saturation scaler based on minimizing a saturation cost function, wherein the saturation cost function is based on a difference measure between the first saturation values and scaled second hue values; and generating a scaling vector based on the saturation scaler. 2. The method of claim 1 , further comprising combining the color-rotation matrix and the scaling vector to generate a reshaping color matrix. 3. The method of claim 1 , wherein the first color space comprises a gamma-coded YCbCr color space and the second color space comprises a PQ-coded IPT color space. 4. The method of claim 1 , wherein the first color space comprises a Rec. 709 YCbCr color space and the second color space comprises a Rec. 2020 YCbCr color space. 5. The method of claim 1 , wherein the color-rotation matrix comprises R = [ 1 0 0 0 cos ( a ′ ) sin ( a ′ ) 0 - sin ( a ′ ) cos ( a ′ ) ] , where a′ denotes the hue rotation angle. 6. The method of claim 1 , wherein the scaling vector comprises S = [ 1 b ′ b ′ ] , wherein b′ denotes the saturation scaler. 7. The method of claim 1 , wherein the first color space is the Rec. 709 YCbCr color space, the second color space is the ST 2084 IPT color space (IPT-PQ) and the color-rotation matrix comprises R = [ 1 0 0 0 0.3133 0.9496 0 - 0.9496 0.3133 ] . 8. The method of claim 2 , wherein the reshaping color matrix comprises: R S = [ 1 0 0 0 cos ( a ′ )
Adaptive-dynamic-range coding [ADRC] · CPC title
using pre-processing or post-processing specially adapted for video compression · CPC title
Embedding additional information in the video signal during the compression process (H04N19/517, H04N19/68, H04N19/70 take precedence) · CPC title
Colour space transformation · CPC title
involving scene cut or scene change detection in combination with video compression · CPC title
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