Rice Parameter Clipping for High Bit Depth Video Coding
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Solution Overview
Problem
Existing video coding standards, such as ITU-T H.266/Versatile Video Coding (VVC), face challenges in efficiently coding high bit depth video data due to limitations in the clipping function for Rice parameter values, leading to increased codeword sizes and data signaled in the bitstream when bit depth exceeds 10 bits.
Innovation Solution
The proposed solution involves calculating a base level offset value based on the bit depth and slice type, normalizing the sum of absolute values of neighboring coefficients, and using this normalized value to determine a Rice parameter, which is then used to binarize the current coefficient, ensuring the Rice parameter remains within a suitable range for efficient coding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the Rice parameter is not clipped for high bit depth video data, then the coding precision is improved, but the codeword size and data signaled in the bitstream increase
Solution Approach 1:
The patent applies parameter changes by introducing a clipping function that modifies the Rice parameter values based on bit depth thresholds. When bit depth exceeds 10 bits, the Rice parameter is clipped to a maximum value (e.g., 3), transforming the parameter range to maintain efficient coding. This resolves the contradiction by adapting the parameter range dynamically based on bit depth conditions.
Solution Approach 2:
The patent implements dynamics by making the Rice parameter derivation adaptive rather than static. The clipping behavior dynamically adjusts based on the bit depth of the video data, allowing the system to optimize between precision and codeword size depending on the specific application requirements. This dynamic adaptation resolves the fixed contradiction between precision and data volume.
2Measurement precision
If the Rice parameter range is extended for high bit depth video data, then the coding accuracy is improved, but the complexity of the coding process increases
Solution Approach 1:
The patent changes the parameter derivation approach by introducing bit depth-based clipping rules. Instead of allowing the Rice parameter to grow unbounded with bit depth, the system applies a clipping function that limits the parameter range while maintaining coding accuracy through conditional logic. This simplifies the overall process compared to handling arbitrarily large parameter values.
Solution Approach 2:
The patent segments the Rice parameter derivation process into distinct cases based on bit depth thresholds. By dividing the parameter space into manageable ranges (e.g., bit depth ≤ 10 vs. bit depth > 10), the system avoids the complexity of handling a single continuous parameter space, making the coding process more tractable while maintaining accuracy.
3Quantity of substance
If the Rice parameter is clipped to a fixed range, then the codeword size is reduced, but the adaptability to different bit depths decreases
Solution Approach 1:
The patent restores adaptability through dynamic clipping thresholds that adjust based on bit depth. Rather than using a fixed clipping range for all scenarios, the system modifies the clipping behavior according to the specific bit depth of the input video data. This dynamic approach maintains both data efficiency and adaptability across different high bit depth scenarios.
Solution Approach 2:
The patent creates a universal clipping mechanism that handles multiple bit depth scenarios through a single adaptive function. The clipping function serves multiple purposes: it reduces codeword size when needed, maintains precision when appropriate, and adapts to various bit depth configurations. This multi-functional approach resolves the contradiction between fixed-range efficiency and adaptability.
Data Source
AI summary
An example device for coding (encoding and/or decoding) video data includes a memory configured to store video data; and one or more processors implemented in circuitry and configured to: calculate a sum of absolute values of a plurality of neighboring coefficients to a current coefficient for a current block of video data; calculate a base level offset value according to at least one of a bit depth for the video data or a slice type for a slice including the current block; calculate a normalized value for the sum of absolute values using the base level offset value; and code the current coefficient using the normalized value for the sum of absolute values.