Video Quantization Glare Masking Adaptation
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Solution Overview
Problem
Existing video encoding and decoding methods for HDR videos fail to effectively address glare masking effects, leading to inefficient compression and visual quality issues due to the human visual system's reduced sensitivity to dark areas around bright regions.
Innovation Solution
A method and apparatus that adjust quantization parameters based on the glare masking effect by calculating a glare factor and using Just Noticeable Difference (JND) metrics to determine optimal quantization ratios, allowing for coarser quantization in dark areas and improving compression efficiency while preserving visual quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If uniform quantization is applied to all blocks regardless of luminance, then encoding complexity is reduced, but visual quality deteriorates in dark areas near bright regions due to glare masking effects
Solution Approach 1:
The patent applies different quantization parameters to different blocks based on their luminance characteristics and glare masking effects. Specifically, blocks adjacent to bright regions with high glare factors receive coarser quantization, while other blocks maintain finer quantization. This local adaptation resolves the contradiction by optimizing visual quality where needed without uniformly increasing encoding complexity across the entire video stream.
Solution Approach 2:
The quantization parameter is dynamically adjusted based on calculated glare factors for each block. The encoder computes luminance values, determines glare factors using equations that consider neighboring block luminance, and adapts quantization parameters accordingly. This dynamic adjustment allows the system to respond to local visual characteristics, improving quality in critical regions while maintaining efficiency elsewhere.
2Productivity
If coarser quantization is applied in dark areas affected by glare masking, then compression efficiency is improved, but visual quality in those specific areas deteriorates
Solution Approach 1:
The patent exploits the glare masking effect - a physiological limitation of the human visual system - to improve compression efficiency. By calculating glare factors and applying coarser quantization in dark areas adjacent to bright regions where the human eye is less sensitive, the system converts a visual weakness into a compression advantage. The visual quality deterioration is acceptable and imperceptible in these specific regions, while overall compression efficiency improves.
3Manufacturing precision
If quantization parameters are adjusted based on glare masking effects, then visual quality is improved, but computational complexity increases due to additional luminance calculations and glare factor determination
Solution Approach 1:
The patent performs preliminary calculations of luminance values and glare factors during the encoding process before final quantization. By pre-computing these parameters and storing them for reference, the system avoids redundant calculations and streamlines the subsequent quantization decision-making process. This preliminary action reduces the overall computational burden while maintaining the benefits of adaptive quantization.
Data Source
AI summary
Because human eyes may become less sensitive to dark areas around very bright areas in a video (known as glare masking), we may use coarser quantization in such dark areas. Considering the extra distortion that human eyes can tolerate in a block with glare masking, a quantization ratio for the block can be calculated. The quantization parameter for the block can then be scaled up using the quantization ratio to form an adjusted quantization parameter. In one embodiment, the adjusted quantization parameter can be derived at the decoder side, and thus, transmission of quantization ratio information is not needed. In particular, we can estimate the luminance of a current block based on a predicted block and de-quantized DC coefficient, and use the luminance of causal neighboring blocks and the estimated luminance of the current block to estimate the adjusted quantization parameter.