Block Type Selection for Video Compression
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Solution Overview
Problem
Current video compression methods, such as the H.264 standard, require numerous computations to determine the best block types for macroblocks, which can be inefficient and time-consuming, especially when dealing with multiple motion vectors and various block sizes.
Innovation Solution
A method and apparatus that partition a macroblock into M×N blocks, combine adjacent blocks into composite blocks, calculate image characteristics and motion vectors for both block types, and select a participation member based on cost values to optimize block type configuration for compression, reducing the computational burden and improving encoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple motion vectors and various block sizes are evaluated for each macroblock, then encoding quality is improved, but computational complexity increases significantly
Solution Approach 1:
The patent divides the macroblock evaluation process into two stages: first evaluating a limited set of candidate block types (16×16, 8×16, 16×8, 8×8) to identify promising regions, then selectively evaluating smaller block types (4×4, 4×8, 8×4) only in regions where the coarse evaluation indicates potential benefits. This hierarchical segmentation reduces the total number of computations while preserving encoding quality.
Solution Approach 2:
The patent applies different evaluation strategies to different regions of the macroblock. Regions with high motion activity or texture complexity undergo more thorough evaluation with multiple motion vectors and smaller block types, while homogeneous regions use simpler evaluation. This local differentiation optimizes computational resources based on actual content requirements.
2Productivity
If comprehensive block type evaluation is performed for all macroblocks, then compression efficiency is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary evaluation using a subset of block types and motion vectors before committing to full evaluation. By pre-identifying regions that benefit from detailed analysis, the system avoids unnecessary computations in regions where simple block types suffice, thereby reducing overall processing time while maintaining compression efficiency.
Solution Approach 2:
The patent applies partial evaluation strategies where only necessary block types and motion vectors are computed for each macroblock region. Instead of universally evaluating all possible block types, the system performs partial evaluations based on regional characteristics, reducing processing time while achieving sufficient compression efficiency through selective application of more expensive operations.
Data Source
AI summary
Devices, systems, methods, and other embodiments associated with block type selection are described. In one embodiment, a method calculates for each block from a set of M×N blocks that form a macroblock of image data, a first set of data. Adjacent blocks of the set of M×N blocks are combined into composite blocks. Data of the first set of data is selectively forwarded to composite blocks. For each composited block, a second set of data is calculated based, at least in part, on the forwarded data. A participation block is selected from one of the set of M×N blocks and the set of composite blocks based, at least in part, on the first set of data and the second set of data. The macroblock is compressed based on the participation block.