Motion Estimation Distortion Compression for Video Encoding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Highly accurate motion-compensated prediction algorithms in video encoding are prohibitively expensive in terms of computational complexity and memory bandwidth, and existing methods to reduce memory requirements come at the cost of high storage needs for distortion values.
Innovation Solution
A method to compress distortion information for motion estimation by determining and storing distortion values for each trial motion vector, using a fixed number of bits based on the minimum distortion value, and re-storing compressed values, which reduces storage capacity and computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If highly accurate motion-compensated prediction algorithms are used, then motion estimation accuracy is improved, but computational complexity and memory bandwidth requirements increase prohibitively
Solution Approach 1:
The patent segments the distortion values into multiple groups based on their magnitude ranges. Each group is handled separately with appropriate compression strategies, allowing accurate representation of small distortion values while efficiently managing large distortion values, thus reducing overall computational complexity without sacrificing motion estimation accuracy.
Solution Approach 2:
The patent transforms distortion values from their original linear representation to a compressed representation using logarithmic or exponential scaling. This parameter change allows the same amount of data to represent a much wider range of distortion values, reducing the memory bandwidth and computational complexity required while maintaining the precision needed for accurate motion estimation.
2Measurement precision
If merge-based strategies with variable block sizes are used, then motion estimation accuracy at low computational complexity is improved, but storage requirements for distortion values increase
Solution Approach 1:
The patent applies parameter changes by transforming distortion values using logarithmic or exponential functions. This transformation compresses the dynamic range of distortion values, allowing accurate representation of both small and large distortion values using fewer bits, thereby reducing storage requirements while maintaining motion estimation accuracy for variable block sizes.
Solution Approach 2:
The patent merges multiple distortion value groups into a unified compressed representation. By grouping distortion values based on their magnitude and applying consistent compression strategies across groups, the patent reduces the total storage requirements while maintaining the accuracy needed for comparing different block sizes in merge-based motion estimation.
3Measurement precision
If distortion values are stored for every possible combination of block size and motion vector, then motion estimation accuracy is improved, but memory bandwidth and storage capacity requirements increase
Solution Approach 1:
The patent changes the parameter representation of distortion values from linear to logarithmic/exponential scale. This allows the system to store and process distortion values with much higher efficiency, reducing memory bandwidth requirements while maintaining the precision necessary for accurate motion estimation across all block sizes and motion vectors.
Solution Approach 2:
The patent performs preliminary compression of distortion values before they are stored or processed further. By applying compression transformations to distortion values in advance, the system reduces the memory bandwidth required for subsequent processing and storage operations, while the compressed values retain sufficient precision for accurate motion estimation.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Disclosed is a low-complexity and yet efficient lossy method to compress distortion information for motion estimation, resulting in significant reduction in needed storage capacity. A system for implementing the method and a computer-readable medium for storing the method are also disclosed. The method includes determining and storing a distortion value for each trial motion vector in a plurality of trial motion vectors. Each trial motion vector specifies a position of a search region relative to a reference frame. The method further includes compressing each of the distortion values as a fixed number of bits based upon a minimum distortion value amongst the stored distortion values, and re-storing each compressed distortion value in place of its uncompressed value.