Cross-Component Prediction for Video Blocks Under Bandwidth Constraints
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently managing bandwidth demand due to the high data requirements of digital video, particularly in handling chroma and luma components, which can lead to inefficiencies in compression and decoding processes.
Innovation Solution
Implementing cross-component prediction methods, such as Two-Step Cross-component Prediction Mode (TSCPM) and enhanced Cross-component Linear Model (CCLM) coding tools, to optimize the conversion between video blocks and bitstream representations, including adaptive block vector resolution and intra-block-copy modes, while handling scenarios where neighboring reference samples are outside the current video unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If cross-component prediction modes (TSCPM, CCLM) are enabled for all video blocks, then compression performance improves, but bandwidth and processing requirements increase
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the CCP mode selection based on block characteristics. Specifically, it modifies the prediction mode parameters (intra, inter, IBC) and applies CCP selectively rather than universally, changing the operational parameters to optimize the balance between compression ratio and bandwidth usage.
Solution Approach 2:
The patent segments the video processing by dividing blocks into different categories based on their characteristics (non-square blocks, chroma sampling formats). It applies cross-component prediction selectively to specific segments (blocks meeting certain criteria) rather than uniformly to all blocks, thereby reducing overall bandwidth requirements while maintaining compression performance where beneficial.
2Productivity
If enhanced CCP coding tools are used, then video coding efficiency improves, but device complexity increases
Solution Approach 1:
The patent implements dynamic selection of coding tools based on block characteristics. The enhanced CCP tools (TSCPM, CCLM) are not statically applied but dynamically selected based on whether the block is non-square, the chroma sampling format, and other contextual factors. This dynamic approach improves coding efficiency when beneficial while reducing complexity when not needed.
Solution Approach 2:
The patent applies different coding tool qualities to different local regions (video blocks) based on their specific characteristics. Enhanced CCP tools are applied locally to blocks where they provide benefit (non-square blocks, specific chroma formats) rather than uniformly across the entire video stream, optimizing the trade-off between coding efficiency and device complexity.
3Measurement precision
If cross-component prediction is applied to blocks with neighboring reference samples outside current video unit, then prediction accuracy improves, but handling complexity increases
Solution Approach 1:
The patent performs preliminary actions by checking the availability and position of neighboring reference samples before applying cross-component prediction. It pre-determines whether reference samples are within or outside the current video unit and prepares appropriate handling strategies in advance, thereby managing the complexity of cross-boundary prediction while maintaining accuracy.
Data Source
AI summary
Devices, systems and methods for digital video coding, which includes Prediction from Multiple Cross-components (PMC) methods, are described. An exemplary method for video processing includes making a first determination that a cross-component prediction (CCP) mode is disabled for a conversion between a video block of a video and a bitstream representation of the video and making a second determination, based on the first determination, regarding whether a first syntax element indicating usage of an enhanced Two-Step Cross-component Prediction Mode (TSCPM) coding tool or an enhanced cross-component linear model (CCLM) coding tool is included in the bitstream representation. The method also includes performing a conversion based on the second determination.