Video Encoding Quantization Parameter Adjustment for Distortion Control
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Solution Overview
Problem
Current video encoding methods face challenges in accurately measuring and reducing distortion in decoded data while minimizing data size, particularly in lossy compression, where the difference between decoded and original data is significant.
Innovation Solution
The proposed solution involves a video encoding apparatus and method that uses a quantization parameter generator to adjust the quantization parameter based on comparisons with reference values, aiming to increase the structural similarity index (SSIM) or peak signal-to-noise ratio (PSNR) of encoded data, thereby improving the quality index of the encoded data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If lossy compression is applied to reduce data size, then the bitrate of bitstream is reduced, but the difference between decoded data and original data increases
Solution Approach 1:
The patent dynamically adjusts the quantization parameter (QP) based on the variance of original video data. When variance is high (complex regions), a smaller QP is applied to preserve detail and reduce distortion. When variance is low (simple regions), a larger QP is applied to achieve greater compression. This adaptive parameter adjustment resolves the contradiction by optimizing the balance between data size reduction and distortion minimization across different video regions.
2Ease of manufacture
If a fixed quantization parameter is used, then the encoding process is simple, but the quality of encoded data cannot be optimized for different video content
Solution Approach 1:
The patent transitions from a static quantization parameter to a dynamic one that adapts to the local characteristics of video content. The system calculates variance within video blocks and adjusts the QP accordingly, making the encoding process responsive to content complexity. This dynamic adjustment maintains encoding simplicity through automated variance-based rules while significantly improving encoded data quality by matching compression strength to regional requirements.
3Quantity of substance
If quantization is increased to reduce bitrate, then the size of encoded data is reduced, but the distortion in decoded data increases
Solution Approach 1:
The patent applies different quantization strengths to different regions of the video based on local variance characteristics. High-variance regions (containing important details or edges) receive milder quantization to preserve accuracy, while low-variance regions (flat areas) undergo stronger quantization to reduce bitrate. This local differentiation resolves the contradiction by ensuring that bitrate reduction does not compromise the accuracy of visually critical regions.
Data Source
AI summary
According to at least some example embodiments of the inventive concepts, an apparatus for encoding video includes a quantizer configured to, based on a size of an initial quantization parameter of input data, generate output data by quantizing the input data to increase an objective evaluation value of encoded data generated from the output data, or generate the output data by quantizing the input data to increase a subjective evaluation value of the encoded data.