Variable Quantization and Hybrid VLC for Shorter Video Bitstreams
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Solution Overview
Problem
Existing image and video compression methods face inefficiencies in quantization and variable length coding of transform coefficients, particularly in reducing the number of clusters without significantly affecting image quality.
Innovation Solution
The method involves locally variable quantization and context-adaptive hybrid variable length coding, which modifies the quantization of transform coefficients to reduce the number of clusters by applying quantization modifications such as eliminating isolated coefficients and adjusting amplitudes, while using variable length code mappings to encode the positions and amplitudes of clusters efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional fixed quantization is used, then image quality is maintained, but the number of clusters and bitstream length remain large
Solution Approach 1:
The patent applies different quantization strategies to different regions of the transform coefficient block. Specifically, it identifies clusters of non-zero coefficients and applies localized quantization modifications within these clusters while maintaining fixed quantization in other regions. This allows the system to reduce the number of clusters and improve compression efficiency in specific areas without compromising overall image quality.
Solution Approach 2:
The patent modifies quantization parameters dynamically based on the local characteristics of transform coefficients. It changes the quantization step size and quantization matrix values in specific regions to optimize the balance between compression efficiency and image quality. This parameter adaptation allows reducing bitstream length while maintaining perceptual quality.
2Productivity
If the number of clusters is reduced through quantization modification, then bitstream length decreases, but image quality may be affected
Solution Approach 1:
The patent incorporates feedback mechanisms to monitor the impact of quantization modifications on image quality. It uses rate-distortion optimization to evaluate the trade-off between compression efficiency gains and quality loss, adjusting quantization parameters iteratively to find the optimal balance. This feedback-driven approach ensures that cluster reduction does not excessively degrade image quality.
Solution Approach 2:
The patent applies quantization modifications selectively rather than uniformly across the entire coefficient block. It performs partial action by targeting specific clusters for modification while leaving other regions unchanged. This selective approach reduces the overall impact on image quality while still achieving compression efficiency improvements through cluster reduction in critical regions.
3Productivity
If variable length coding is used, then coding efficiency improves, but computational complexity increases
Solution Approach 1:
The patent performs preliminary organization of transform coefficients into clusters before applying variable length coding. By pre-grouping non-zero coefficients and their associated run-length information, it simplifies the subsequent VLC process. This preliminary action reduces the computational complexity of VLC by providing a structured input format that requires less complex decision logic during encoding.
Data Source
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AI summary
A coding method, apparatus, and storage media with instructions to carry out a method. The method operates on an ordered series of transform coefficients of a block of image data, and for a fixed quantization method, and includes quantizing and encoding the ordered series to form a coded bitstream. The quantizing and encoding uses one or more variable length code (VLC) mappings. The quantizing includes quantizing to have amplitude- 1 at least one coefficient that would be quantized by the fixed quantization method to have zero amplitude, quantizing to have zero amplitude at least one coefficient that would be quantized by the fixed quantization method to have amplitude- 1, and using the fixed quantization method to quantize any coefficient that is quantized by the fixed quantization method not to have zero amplitude, amplitude- 1, or amplitude- 2.