Chroma-From-Luma Filter Selection for Better Video Compression
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently selecting downsampling filters for chroma from luma prediction, leading to suboptimal compression efficiency and increased bit usage for less likely intra prediction directions.
Innovation Solution
A method for video processing that involves receiving an input chroma block, applying multiple downsampling filters, iteratively predicting the input chroma block, calculating error scores, and selecting a target downsampling filter based on these scores to enhance compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple downsampling filters are applied and error scores are calculated to select the optimal filter, then compression efficiency is improved, but device complexity and computational overhead increase
Solution Approach 1:
The patent pre-calculates and stores error scores for different downsampling filters and intra prediction directions during an encoding phase. These pre-computed error scores are then reused during decoding, eliminating the need for real-time complex calculations and reducing computational overhead while maintaining compression efficiency.
Solution Approach 2:
The system uses the calculated error scores to automatically select the optimal downsampling filter without requiring external intervention or complex decision-making processes. The error scores inherently guide the filter selection, making the system self-optimizing.
2Loss of information
If optimal downsampling filter selection is implemented, then bit usage for less likely directions is reduced, but encoding complexity increases
Solution Approach 1:
The patent performs preliminary encoding passes to calculate error scores for different filter-direction combinations before final encoding. This pre-computation allows the system to identify the most efficient filter-direction pairs in advance, reducing bit usage while managing encoding complexity through staged processing.
Solution Approach 2:
The system dynamically adjusts the selection of downsampling filters and intra prediction directions based on calculated error scores. By changing parameters (filter type, direction) according to computed metrics, the system optimizes bit usage efficiency while maintaining manageable encoding complexity through systematic parameter selection.
Data Source
AI summary
This disclosure relates to video processing that includes iteratively predicting a chroma block in a Chroma from Luma (CfL) prediction mode based on downsampled luma samples downsampled from a plurality of downsampling filters, and selecting a target downsampling filter from the plurality of downsampling filters that corresponds to an error score determined for the iteratively predicting.