High-Level Weighted Prediction Signaling for Reduced Video Bitstream Volume
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Solution Overview
Problem
Existing video coding techniques face challenges in achieving efficient compression with minimal quality loss, particularly in handling illumination changes using weighted prediction tools like H.264, which can be improved by optimizing the coding order and binarization of syntax elements.
Innovation Solution
The proposed method involves reordering syntax elements to include high-level syntax weighted prediction parameters and coding the reference picture list structure based on these parameters, with restrictions on binarization to reduce the amount of coded weighted prediction parameters, especially when delta POC values are zero.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional H.264 weighted prediction coding is used, then illumination changes can be compensated, but the amount of coded data increases reducing compression efficiency
Solution Approach 1:
The patent extracts and removes redundant syntax elements from the weighted prediction coding process. Specifically, it eliminates the need to code reference picture list structure when delta POC values are zero, and removes unnecessary binarization operations for certain syntax elements. This extraction of unnecessary components reduces the amount of coded data while preserving the essential illumination compensation functionality.
Solution Approach 2:
The patent applies partial action by conditionally applying weighted prediction coding only when necessary (when delta POC values are non-zero). When delta POC equals zero, the patent skips the coding of reference picture list structure entirely. This selective application reduces overall coded data volume while maintaining compensation accuracy where needed.
2Measurement precision
If weighted prediction parameters are coded for all reference pictures, then prediction accuracy is improved, but coding complexity and data volume increase
Solution Approach 1:
The patent applies local quality by differentiating the coding treatment based on local characteristics of reference pictures. When delta POC values are zero, the patent uses a simplified coding approach (skipping reference picture list structure coding), while when delta POC values are non-zero, the full weighted prediction coding is applied. This localized adaptation of coding complexity matches the actual prediction needs.
Solution Approach 2:
The patent changes the coding parameters dynamically based on delta POC values. The syntax element coding is conditioned on the delta POC parameter, allowing the system to switch between full-precision coding and simplified coding modes. This parameter-based adaptation reduces coding complexity while maintaining prediction accuracy where required.
3Measurement precision
If full binarization of reference picture list structure is applied, then decoding accuracy is ensured, but bitstream volume increases
Solution Approach 1:
The patent extracts and removes unnecessary binarization operations from the encoding process. Specifically, when delta POC values are zero, the patent eliminates the binarization of reference picture list structure syntax elements entirely. This extraction of redundant binarization operations reduces bitstream volume while maintaining sufficient decoding accuracy through alternative signaling methods.
Data Source
AI summary
The present disclosure provides an encoding method, wherein the method comprises: determining syntax elements to be coded, wherein the syntax elements include a reference picture list structure and at least one high-level syntax (HLS) weighted prediction parameters; coding the at least one HLS weighted prediction parameters; and after coding the at least one HLS weighted prediction parameters, coding the reference picture list structure. The syntax elements are reordered such that coding the reference picture list structure can be based on values of the at least one HLS weighted prediction parameters.