Weighted Picture Filtering for Blurring and Ringing in Video Coding
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Solution Overview
Problem
Current video coding schemes, such as H.265/HEVC and H.266/VVC, lack filters that effectively address blurring and ringing artifacts, leading to increased coding costs and reduced picture quality.
Innovation Solution
A method involving a decoder and encoder that applies a weighted filter with spatially varying weights to address blurring and ringing artifacts, using a weighting map function and filter within the coding loop to enhance picture quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If linear filters are applied to recover blurred content, then picture quality is improved, but ringing artifacts and noise amplification occur
Solution Approach 1:
The patent applies different filter types (luma filter and chroma filter) to different color channels based on local picture characteristics. The luma filter addresses blurring in luminance information while the chroma filter handles chrominance information, allowing tailored filtering for each channel's specific needs and reducing artifacts.
Solution Approach 2:
The filtering process is segmented into separate luma and chroma filtering operations. By dividing the picture into different color channels and applying appropriate filters to each, the system can address blurring without causing ringing artifacts that would affect the entire picture uniformly.
2Manufacturing precision
If multiple filters are applied to address different coding errors, then picture quality is improved, but coding costs increase
Solution Approach 1:
The patent implements a unified filtering framework that handles multiple types of coding errors (blurring, ringing artifacts, blocking artifacts) through a single adaptive loop filter structure. This multi-functional filter replaces the need for multiple separate filters, reducing coding complexity while maintaining comprehensive error correction.
Solution Approach 2:
The filter adapts its parameters based on local picture characteristics and coding conditions. By dynamically adjusting filter strength and type according to the specific error types present in different regions, the system achieves high picture quality without requiring multiple fixed filters, thus reducing overall coding costs.
3Manufacturing precision
If adaptive loop filter with multiple classes is used to deal with noise amplification, then picture quality is improved, but signaling costs increase
Solution Approach 1:
The patent applies content-adaptive filtering where filter parameters are determined by local picture characteristics such as edge strength and texture complexity. This allows the filter to adapt to local noise conditions without requiring extensive signaling, as the adaptation is based on locally available picture information rather than transmitted class labels.
Solution Approach 2:
The filtering system uses the picture's own characteristics (luma and chroma components) to determine filtering parameters. The filter adapts automatically based on the input picture content, eliminating the need for external signaling of class information while still achieving noise amplification control through self-adaptation.
Data Source
AI summary
A method of processing video data, performed by a decoder, is provided. The method includes decoding a bitstream to obtain video data and coding information; obtaining a picture based on the video data; determining a weighting map using a weighting map function, the weighting map comprising a plurality of weights mapped to respective spatial locations of the picture, wherein the picture and/or coding information are used as inputs to the weighing map function; determining a filter; and applying the weighting map and the filter to the picture to obtain a filtered picture.