Piecewise-linear inter-layer predictor for HDR video coding
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Solution Overview
Problem
Current methods for coding and delivering high-dynamic range (HDR) images suffer from artifacts such as banding, blocking, and color bleeding, particularly in low bit rate scenarios due to the non-linear response of the human visual system and limitations in existing prediction techniques.
Innovation Solution
A piecewise-linear inter-layer predictor is employed to adjust the slope of the prediction function based on scene-significance histograms, masking residuals to improve encoding efficiency and reduce artifacts, while maintaining a low bit rate for the enhancement layer, and is compliant with existing Dolby Vision decoders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing prediction techniques are used for HDR video coding, then encoding simplicity is maintained, but visual quality deteriorates due to artifacts such as banding, blocking, and color bleeding
Solution Approach 1:
The prediction function is divided into multiple linear segments with different slopes, allowing different regions of the dynamic range to be predicted with different characteristics. This segmentation enables better adaptation to the non-linear response of the human visual system while avoiding the artifacts produced by uniform prediction approaches.
Solution Approach 2:
Different segments of the prediction function are assigned different slopes tailored to specific luminance ranges. This local optimization allows the predictor to match the human visual system's non-linear response in different brightness regions, improving visual quality and reducing artifacts like banding and color bleeding in specific areas.
2Manufacturing precision
If enhancement layer data is increased to improve visual quality, then HDR video quality improves, but bit rate increases
Solution Approach 1:
The prediction function parameters (slopes of different segments) are optimized to minimize the enhancement layer data required. By carefully selecting segment slopes that match the human visual system's characteristics, the residual error is reduced, allowing lower bit rates in the enhancement layer while maintaining high visual quality.
3Manufacturing precision
If piecewise-linear prediction is implemented, then visual quality and artifact reduction are improved, but computational complexity increases
Solution Approach 1:
The piecewise-linear function divides the prediction into multiple segments, each with simple linear calculations. While this improves visual quality by adapting to different luminance ranges, it does increase computational complexity compared to a single linear predictor. The complexity is managed by limiting the number of segments and using efficient calculation methods.
Data Source
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AI summary
In a method to improve the dynamic range of high-dynamic range (HDR) signals using an enhancement layer, a piecewise-linear inter-layer predictor and a residual masking operator are applied. The generation of the piecewise-linear inter-layer prediction function is based on a computed scene-significance histogram based on the average of frame-significance histograms indicating pixel values where coding artifacts are most likely to occur. For each segment in the prediction function, its slope is inversely proportional to a measure of energy in the segment under the scene-significance histogram. Bit rate constrains for the enhancement layer are also taken into consideration in determining the piecewise-linear prediction function.