| CPC H04N 19/98 (2014.11) [G06T 5/90 (2024.01); H04N 19/186 (2014.11); H04N 19/46 (2014.11); G06T 2207/20208 (2013.01)] | 11 Claims |

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1. A method for decoding high-dynamic range images and video, the method comprising:
receiving an input image represented in an input dynamic range;
receiving metadata for the input image to generate a mapping function to map the input image from the input dynamic range to an output image in an output dynamic range;
parsing a first metadata parameter to identify whether a second metadata parameter is present;
if the second metadata parameter is present, then
generating the mapping function using a non-backward compatible predictor, wherein the non-backward compatible predictor comprises a tensor-product B-spline (TPB) predictor, wherein generating the mapping function using a tensor-product B-spline (TPB) predictor comprises:
accessing TPB metadata within the metadata of the input image, wherein the TPB metadata comprise TPB-related prediction parameters, prediction coefficients, and auxiliary data; and
generating based on the TPB metadata a three dimensional look up table (3D-LUT) to map selected triplets of pixel values in the input dynamic range to corresponding output triplets of pixel values in the output dynamic range,
wherein generating the 3D-LUT involves, for each 3D-LUT index, generating respective basis functions by using the prediction parameters and computing a respective output pixel value by using the prediction coefficients based on the basis functions;
wherein generating the 3D-LUT involves first storing frequently used values of the basis functions in one or more 2D arrays for later computing output pixel values by using the prediction coefficients;
wherein the prediction parameters comprise:
a number of knot points (T) in each of three dimensions of a luma channel and two chroma channels; and
polynomial order (l) values in each of the three dimensions of the luma channel and the two chroma channels;
wherein the prediction coefficients comprise:
prediction coefficients for the luma channel and the two chroma channels; and
wherein the auxiliary data comprise:
a luma-channel basis flag and two chroma-channel basis flags for determining correlation among the prediction coefficients for the luma channel and the two chroma channels;
else generating the mapping function using a backward-compatible predictor supported by legacy devices; and
applying the mapping function to the input image to generate the output image,
wherein the input dynamic range comprises a standard dynamic range and the output dynamic range comprises a high dynamic range.
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