Non-uniform Reconstruction Space for Video Quantization
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Solution Overview
Problem
Current video encoding standards, such as H.264, use uniform quantization step sizes, which do not always achieve optimal rate-distortion performance due to assuming a uniform distribution of data points, leading to suboptimal compression efficiency.
Innovation Solution
Implementing a non-uniform reconstruction space in both the encoder and decoder, where the reconstruction level is adjusted based on the actual distribution of data points, allowing for adaptive quantization that minimizes distortion while optimizing coding rate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If uniform quantization step size is used, then encoding simplicity is maintained, but rate-distortion performance deteriorates
Solution Approach 1:
The patent applies local quality by using different quantization step sizes for different regions or coefficient positions in the transform domain. Instead of a single uniform step size, the quantizer adapts the step size locally based on the characteristics of the data distribution in different regions, thereby improving rate-distortion performance while maintaining reasonable encoding complexity.
Solution Approach 2:
The patent introduces dynamic quantization where the quantization step size is not fixed but adapted based on the actual data distribution. The quantizer dynamically selects or calculates appropriate step sizes according to the statistical properties of the transform coefficients, allowing the system to optimize performance for different content types and regions.
2Device complexity
If uniform partitioning of data space is used, then quantization process is simplified, but reconstruction accuracy deteriorates
Solution Approach 1:
The patent implements local quality in the reconstruction space by using non-uniform reconstruction levels that are tailored to different regions of the data space. The reconstruction values are adjusted locally to match the actual distribution of quantized coefficients, improving reconstruction accuracy without requiring complex global transformations.
Solution Approach 2:
The patent changes the parameters of the reconstruction space from uniform to non-uniform. By modifying the reconstruction levels and step sizes based on the actual data distribution characteristics, the system achieves better reconstruction accuracy while keeping the quantization framework relatively simple.
Data Source
AI summary
An encoding method for encoding video data by adjusting a quantization parameter, the video data being partitioned into blocks comprising sets of quantized transform coefficients. The method includes, for a set of quantized transform coefficients corresponding to one of the blocks, collecting statistics, wherein the statistics comprise the number of quantized transform coefficients and the sum of the non-rounded quantization value of the quantized transform coefficients in the set. The method also includes deriving a step size based on the statistics, mapping the derived step size to a closest quantization parameter value, and quantizing a next block using the mapped quantization parameter value.