Quantization Matrix Subsetting for Video Encoder Efficiency
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Solution Overview
Problem
Existing video coding technologies face challenges in improving coding efficiency, enhancing image quality, and reducing circuit scale while managing processing resources effectively.
Innovation Solution
The proposed solution involves an encoder that generates a quantization matrix with a subset of matrix elements and quantizes transform coefficients based on threshold x and y-coordinate values, allowing for efficient encoding and decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a full quantization matrix is used for all transform coefficients, then quantization accuracy is improved, but processing complexity and circuit scale increase
Solution Approach 1:
The quantization matrix is segmented into multiple subsets based on coordinate thresholds. The encoder divides the matrix into different regions (e.g., low-frequency and high-frequency components) and applies different quantization strategies to each subset, reducing the overall complexity while maintaining accuracy where needed.
Solution Approach 2:
Different quantization precision levels are applied to different regions of the transform coefficient matrix. Low-frequency coefficients (important for image quality) use higher precision quantization, while high-frequency coefficients (less important) use lower precision, optimizing the balance between quality and complexity.
2Productivity
If more processing resources are allocated to encoding operations, then coding efficiency is improved, but hardware resource utilization increases
Solution Approach 1:
The encoder applies full processing resources only to the necessary subset of coefficients that contribute most to coding efficiency. By identifying and processing only the critical coefficients (those within threshold coordinates), the system achieves high coding efficiency without allocating resources to process all coefficients equally.
3Device complexity
If a subset of quantization matrix elements is used, then circuit scale is reduced, but quantization performance may deteriorate
Solution Approach 1:
The encoder performs preliminary analysis to identify which quantization matrix elements are most important for the current block characteristics. Based on this preliminary assessment, it selects an appropriate subset of matrix elements to use, ensuring that the most critical elements are included while excluding less important ones, thus maintaining performance with reduced complexity.
Data Source
AI summary
Various embodiments provide an encoder that generates a plurality of quantization matrix elements for a current block; generates a quantization matrix using the plurality of quantization matrix elements; and quantizes, using the quantization matrix, transform coefficients of the current block. The quantization matrix includes only a subset of quantization matrix elements of the plurality of quantization matrix elements. Each of the subset of quantization matrix elements has an x-coordinate value less than a threshold x-coordinate value, a y-coordinate value less than a threshold y-coordinate value, or an x-coordinate value less than the threshold x-coordinate value and a y-coordinate value less than the threshold y-coordinate value.