Video Decoder Transform Selection via Predictive Block Characteristics
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Solution Overview
Problem
Current video encoding and decoding technologies face challenges in efficiently signaling transforms for residual data, leading to increased bandwidth usage and computational overhead.
Innovation Solution
The proposed solution involves determining transform information at both video encoders and decoders to enable transform signaling with minimal or no explicit signaling, allowing for reduced bandwidth usage and improved efficiency by identifying characteristics of predictive blocks to select appropriate transforms for residual data coding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If explicit signaling is used to indicate transforms for residual data, then transform selection flexibility is improved, but signaling overhead and bandwidth usage increase
Solution Approach 1:
The decoder determines the transform type for residual data by analyzing characteristics of the predictive block itself, without requiring explicit signaling from the encoder. The transform selection is self-determined based on block characteristics such as prediction mode, block size, and gradient calculations, eliminating the need for additional signaling bits.
Solution Approach 2:
The patent changes the approach from signaling transform parameters explicitly to deriving transform parameters from other block characteristics. By calculating gradients and analyzing predictive block properties, the transform type is determined through parameter analysis rather than direct signaling, reducing bandwidth requirements.
2Productivity
If multiple transform types are supported for different residual data characteristics, then coding efficiency is improved, but device complexity increases
Solution Approach 1:
The patent introduces gradient-based parameters to characterize the predictive block and uses these parameters to select from multiple transform types. By calculating gradients in different directions and comparing them, the system automatically selects the most appropriate transform (DST-VII, DCT-II, or skipped) without requiring complex decision logic.
Solution Approach 2:
Different transform types are applied to different regions or blocks based on their local characteristics. The gradient analysis is performed locally for each predictive block, allowing the transform selection to be adapted to local image features such as edges, textures, and smooth regions, thereby improving coding efficiency for diverse content types.
3Loss of information
If transform signaling is reduced or eliminated, then bandwidth usage is reduced, but transform selection accuracy may worsen
Solution Approach 1:
The system uses gradient calculations and block characteristic analysis as feedback mechanisms to determine the optimal transform type. By continuously analyzing the predictive block properties and using this information to select transforms, the system maintains high transform selection accuracy without requiring explicit signaling, effectively using the block characteristics themselves as feedback for transform determination.
Data Source
AI summary
A device for video coding is configured to determine a characteristic of a predictive block of a current block of a current picture; identify a transform for decoding the current block based on the characteristic; inverse transform coefficients to determine a residual block for the current block; and add the residual block to a predictive block of the current block to decode the current block.