Pixel Selection Pattern Matrix for Video Coding Metric Computation
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Solution Overview
Problem
Existing motion compensated video coding methods are computationally intensive due to the high cost of calculating metrics for comparing image blocks, particularly in the movement estimation phase, which is exacerbated by increasing video resolution and resource constraints in heterogeneous networks.
Innovation Solution
A method and system that generate a pattern matrix to select a subset of pixels for computing a metric, utilizing CPU architecture-specific pattern matrices and global motion characteristics to reduce computational complexity by applying Sum of Absolute Differences or Mean Squared Error functions only to selected pixels, thereby optimizing the computation of the metric.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full pixel computation is used for metric determination, then measurement precision is improved, but computational complexity increases
Solution Approach 1:
The image block is segmented into a grid pattern where only specific pixels (e.g., corner pixels, edge pixels, or pixels at regular intervals) are selected for metric computation. This segmentation approach maintains measurement precision by strategically choosing representative pixels while significantly reducing the total number of computations required for SAD or MSE calculations.
Solution Approach 2:
Different regions of the image block are treated with different computation qualities. The patent applies selective pixel sampling where certain local regions (such as boundaries or high-variation areas) may use full pixel computation while other regions use reduced sampling, optimizing the balance between accuracy and computational load based on local image characteristics.
2Measurement precision
If full pixel computation is used for metric determination, then measurement precision is improved, but processing time increases
Solution Approach 1:
By segmenting the pixel set into a pattern matrix that selects only necessary pixels for computation, the patent reduces the number of arithmetic operations required for each metric calculation. This segmentation enables faster processing while maintaining acceptable accuracy by focusing computations on pixels that contribute most to motion estimation accuracy.
Solution Approach 2:
The patent applies partial action by computing the metric using only a subset of pixels rather than all pixels in the block. This partial computation is sufficient for achieving the required measurement precision in motion estimation, thereby reducing processing time without excessive loss of accuracy.
3Measurement precision
If comprehensive pixel analysis is performed, then metric accuracy is improved, but energy consumption increases
Solution Approach 1:
The segmentation of pixels into a pattern matrix reduces the number of arithmetic operations (additions, multiplications, and memory accesses) required for metric computation. This directly reduces energy consumption in resource-constrained devices while maintaining sufficient metric accuracy for motion estimation through strategic pixel selection.
Data Source
AI summary
Method and system for determination of a metric measuring a difference between two image blocks used in motion compensated video coding of scenes are described. Only selected pixels in a block in the scene are processed for enhancing the speed of the metric computation.