Video Encoder Quantization Parameter Adaptation for HDR
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Solution Overview
Problem
Current video coding standards, such as HEVC, do not adequately exploit flexibility to adapt to the statistical characteristics of High Dynamic Range (HDR) content, leading to inefficiencies in encoding variations present in HDR compared to Standard Dynamic Range (SDR) content.
Innovation Solution
The method involves calculating a quantization parameter change for color components in a block of samples based on statistics from a larger source block, allowing for dynamic adjustment of quantization parameters to optimize encoding, which can be signaled to a decoder, enabling more efficient compression of HDR content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If current video coding standards (HEVC) are used without adaptation, then encoding simplicity is maintained, but compression efficiency for HDR content deteriorates
Solution Approach 1:
The patent implements dynamic quantization parameter adjustment by calculating QP changes based on statistics from larger source blocks and applying them to smaller coding blocks. This dynamic adaptation allows the encoder to optimize compression efficiency for HDR content's statistical characteristics while maintaining a relatively simple base structure built on existing HEVC frameworks.
Solution Approach 2:
The patent changes the quantization parameter values adaptively based on content statistics. By calculating QP changes from source block statistics and applying offsets to base QP values, the system optimizes compression for HDR content without fundamentally altering the video coding standard structure, thus improving productivity with controlled complexity increase.
2Manufacturing precision
If uniform quantization parameters are used across all blocks, then encoding simplicity is maintained, but encoding precision for HDR statistical characteristics deteriorates
Solution Approach 1:
The patent applies different quantization parameters to different coding blocks based on local content statistics. By calculating QP changes from source block statistics and applying them locally to each coding block, the system achieves higher encoding precision for HDR content while limiting complexity through the use of a systematic QP change calculation method rather than completely independent per-block optimization.
Solution Approach 2:
The patent segments the video content into source blocks and coding blocks, allowing different quantization strategies to be applied at different levels. The source block statistics are used to derive QP changes that are then applied to smaller coding blocks, enabling precise local adaptation without requiring complex per-pixel or per-coefficient quantization management.
3Productivity
If quantization parameters are adapted to HDR statistical characteristics, then compression efficiency is improved, but the complexity of quantization parameter calculation increases
Solution Approach 1:
The patent performs preliminary calculation of quantization parameter changes from source block statistics before the actual encoding of coding blocks. By pre-calculating QP offsets based on source block characteristics and then applying them to subsequent coding blocks, the system improves compression efficiency while managing complexity through systematic reuse of calculated values rather than repeated calculations for each block.
Solution Approach 2:
The patent copies and reuses quantization parameter change values across multiple coding blocks that share similar statistical characteristics. By deriving QP changes from source block statistics and applying them to corresponding coding blocks, the system achieves compression efficiency improvements without the full complexity of independent optimization for each block, effectively copying successful parameter settings across similar content regions.
Data Source
AI summary
There are provided mechanisms for encoding a picture of a video sequence in a video bitstream. The picture comprises a first block of samples, wherein each sample in the first block of samples has sample values associated with at least a luma color component and a chroma color component. Each color component is assigned a first quantization parameter. The method comprises calculating a quantization parameter change for at least one color component in the first block of samples, with respect to the first quantization parameter, based on statistics calculated from the sample values from at least one color component in a second block of samples. The second block of samples is one of: source samples of the first block of samples and source samples larger than the first block of samples including the first block of samples. The method comprises quantizing at least one transform coefficient of a residual for the at least one color component in the first block of samples with a second quantization parameter, wherein the second quantization parameter is equal to the sum of the first quantization parameter and the quantization parameter change for the at least one color component. The method comprises signaling the quantization parameter change for the at least one color component to a decoder.