HDR Color Conversion Correction via Nonlinear Luma Adjustment
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Solution Overview
Problem
Conventional HDR color conversion processes result in artifacts due to chroma subsampling, leading to inaccuracies in reconstructed images, especially in regions with steep nonlinear transfer function slopes, requiring complex and time-consuming iteration methods to correct luma values.
Innovation Solution
A method that adjusts downsampled chroma values using a color conversion application to ensure accurate reconstruction of HDR images by applying a nonlinear opto-electrical transfer function and color transform, allowing for real-time determination of optimal luma values through a single iteration, thereby reducing computational complexity and artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If chroma subsampling is applied to reduce bitrate, then transmission efficiency is improved, but color accuracy deteriorates due to averaging artifacts
Solution Approach 1:
The patent applies preliminary action by adjusting the luma values before chroma subsampling occurs. By modifying the luma component in advance based on the nonlinear transfer function characteristics, the subsequent chroma subsampling and upsampling process preserves color accuracy. This prevents the averaging artifact problem from occurring in the first place, rather than correcting it after damage.
Solution Approach 2:
The patent changes parameters by applying different adjustments to luma values depending on the region of the nonlinear transfer function. In steep slope regions, specific compensation is applied to prevent color shifts. This parameter modification approach allows the system to maintain color fidelity during subsampling while still achieving bitrate reduction through chroma downsampling.
2Manufacturing precision
If conventional iteration methods are used to correct luma values, then color accuracy is improved, but processing time increases significantly
Solution Approach 1:
The patent extracts the essential correction logic from the complex iterative process and implements it as a direct calculation using the nonlinear transfer function characteristics. By taking out only the critical adjustment formula needed for luma correction in steep slope regions, the system achieves color accuracy without the computational overhead of multiple iterations, reducing processing time significantly.
Solution Approach 2:
The correction is performed as a preliminary step before chroma subsampling rather than through post-processing iterations. This preliminary adjustment of luma values based on predetermined transfer function characteristics eliminates the need for time-consuming iterative corrections later, achieving both accuracy and efficiency.
Data Source
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AI summary
One embodiment of the present invention sets forth a technique for correcting color values. The technique includes downsampling first color space values to generate downsampled color space values and upsampling the downsampled color space values to generate second color space values. The technique further includes modifying at least one component value included in the downsampled color space values based on a first component value included in the first color space values, a second component value included in the second color space values, and an approximation of a nonlinear transfer function.