Video Coding Rate-Distortion Estimation Using Hadamard Transform
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Solution Overview
Problem
Conventional video coding systems face high computational complexity and inefficiency in evaluating motion vectors due to the need for full transform, quantization, and entropy coding processes to assess rate and distortion, which limits the evaluation of motion vector candidates.
Innovation Solution
A method that uses a low-complexity Hadamard transform to estimate rate and distortion costs for motion vector candidates, allowing for efficient evaluation without performing the full transform and quantization processes, and subsequently applies a more complex DCT transform for standard-compliant coding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full transform, quantization and entropy coding processes are performed to evaluate each motion vector candidate, then accurate rate and distortion information is obtained, but computational complexity increases significantly
Solution Approach 1:
The patent segments the transform process into two distinct stages: a low-complexity estimation stage using Hadamard transform for motion estimation evaluation, and a high-complexity coding stage using DCT transform for actual encoding. This segmentation allows accurate rate-distortion evaluation during motion estimation without requiring the full complex transform pipeline, thereby resolving the contradiction between evaluation accuracy and computational complexity.
Solution Approach 2:
The patent introduces an intermediary low-complexity Hadamard transform as a mediator between motion compensation and the final DCT transform. This intermediary transform provides sufficient rate-distortion information for motion vector selection while avoiding the computational burden of performing full DCT, quantization and entropy coding for each candidate, thus balancing accuracy and complexity.
2Measurement precision
If full transform and quantization processes are performed for each motion vector candidate, then accurate distortion information is obtained, but processing time increases
Solution Approach 1:
The patent performs preliminary motion estimation using the low-complexity Hadamard transform to identify the best motion vector candidate before applying the full DCT transform and quantization process. This preliminary action narrows down the search space and avoids performing time-consuming full transform and quantization operations on all candidates, thereby reducing processing time while maintaining distortion information accuracy for the selected candidate.
Solution Approach 2:
The patent applies partial action by performing the computationally intensive DCT transform and quantization process only on the selected motion vector candidate rather than all candidates. The Hadamard transform is used for partial evaluation of all candidates, which provides sufficient distortion information for selection without the excessive time cost of full processing on each candidate.
3Productivity
If low complexity Hadamard transform is used for motion estimation, then computational complexity is reduced, but coding performance may be compromised
Solution Approach 1:
The patent segments the transform usage into two functional parts: Hadamard transform for motion estimation and candidate selection, and DCT transform for actual encoding. This segmentation ensures that the low-complexity Hadamard transform is only used where sufficient accuracy is needed for decision-making, while the high-performance DCT transform is reserved for the final encoding step, thus maintaining coding performance while improving encoding efficiency.
Solution Approach 2:
The patent changes the transform parameter (type of transform) based on the processing stage. During motion estimation, it uses Hadamard transform parameters which offer favorable complexity-performance tradeoff. During actual encoding, it switches to DCT transform parameters which provide superior coding performance. This parameter change strategy resolves the contradiction between encoding efficiency and coding performance.
Data Source
AI summary
A method for processing a video signal, comprising the steps of (A) generating a plurality of residual blocks by performing motion compensation on a current block of a video signal comprising a series of frames, where each frame comprises a plurality of blocks, (B) generating a plurality of rate-distortion costs for a plurality of bitstream segments generated for each of the residual blocks using a first transform, (C) determining a residual block having an optimal cost, and (D) transforming the selected block with the optimal cost using a second transform, where the first transform has a lower complexity than the second transform.