Temporal Motion Vector Clipping for Memory-Efficient Image Decoding
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images leads to increased data volume, resulting in higher transmission and storage costs, necessitating improved image encoding/decoding techniques for efficient compression.
Innovation Solution
The method involves clipping and modifying the format of motion vectors to enhance compression efficiency by using a clipped motion vector, scaling, and limiting the dynamic range of motion vectors to reduce memory requirements and computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high resolution and high quality images are used, then image quality is improved, but data volume increases leading to higher transmission and storage costs
Solution Approach 1:
The patent changes the precision parameter of motion vectors by using clipped motion vectors with reduced bit depth (e.g., 6-bit or 8-bit clipping) instead of full precision motion vectors. This parameter change reduces the data volume required to represent motion information while maintaining sufficient encoding accuracy for high resolution images.
Solution Approach 2:
The patent uses simplified motion vector representations (clipped to specific ranges) that require less memory and bandwidth. These clipped motion vectors act as approximate representations that sacrifice some precision for significant reductions in data volume, similar to using simplified models instead of complete detailed representations.
2Measurement precision
If full precision motion vectors are used, then encoding accuracy is improved, but memory space and bandwidth requirements increase
Solution Approach 1:
The patent modifies the precision parameter of motion vectors by clipping them to specific bit depths (6-bit or 8-bit) and limiting their dynamic ranges. This parameter change reduces memory space requirements while maintaining encoding accuracy sufficient for practical applications.
Solution Approach 2:
The patent applies different clipping strategies to different motion vector components and different picture types. For example, it uses 6-bit clipping for some components and 8-bit for others, and applies different clipping ranges for P-frames and B-frames, optimizing the balance between memory usage and encoding accuracy for each specific case.
3Measurement precision
If full precision motion vectors are used, then encoding accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent reduces computational complexity by changing the precision parameter of motion vectors through clipping operations. The clipping process simplifies subsequent calculations involving motion vectors, such as motion compensation and prediction, thereby reducing the overall computational burden while maintaining sufficient encoding accuracy.
4Measurement precision
If full precision motion vectors are transmitted, then decoding accuracy is improved, but bandwidth requirements increase
Solution Approach 1:
The patent transmits motion vectors with clipped precision (6-bit or 8-bit) instead of full precision, directly reducing the bandwidth required to transmit motion information. The clipping is performed in a way that maintains decoding accuracy sufficient for practical applications while achieving significant bandwidth reduction.
Data Source
AI summary
The present specification discloses a method of decoding an image. The method includes obtaining a motion vector of a collocated block included in a reference picture of a current block in a temporal motion buffer; changing a format of the obtained motion vector; and deriving the motion vector, in which the format is changed, into a temporal motion vector of the current block.