Error-Scored Downsampling Filter Selection in Chroma-From-Luma Coding
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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 the best filter based on these scores for encoding, thereby optimizing the downsampling process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple downsampling filters are applied and error scores are calculated to select the best filter, then compression efficiency is improved, but device complexity increases
Solution Approach 1:
The patent applies multiple downsampling filters in advance to generate candidate chroma blocks before final encoding selection. By pre-calculating error scores for each filter option and selecting the best performing filter beforehand, the system optimizes compression efficiency while managing complexity through structured preliminary processing.
Solution Approach 2:
The patent changes the downsampling filter parameters by testing multiple different filters (e.g., different kernel sizes, filter types) and selecting the optimal one based on error scores. This parameter variation approach allows the system to adapt to different content characteristics and achieve better compression without committing to a single fixed filter configuration.
2Loss of information
If multiple downsampling filters are tested and error scores are calculated, then bit usage for less likely intra prediction directions is reduced, but loss of time increases
Solution Approach 1:
The patent applies a limited set of predefined downsampling filters rather than exhaustively testing all possible filters. By selecting a manageable number of candidate filters that are most likely to provide benefit, the system reduces the time required for filter testing while still achieving significant bit usage improvements for less likely intra prediction directions.
Solution Approach 2:
The patent applies different downsampling filters selectively based on the specific intra prediction direction and content characteristics. Rather than uniformly applying the same filter to all cases, the system adapts the filter selection to local requirements, reducing unnecessary processing time for directions where filter variation provides minimal benefit.
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.