Video Encoder Bit Rate Control via Selective Chroma Truncation
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Solution Overview
Problem
Existing video processing systems face challenges in maintaining image decoding quality while adhering to limitations on system memory and bandwidth, as conventional bit rate control methods often result in distorted images when the encoding bit rate reaches its upper limit.
Innovation Solution
An encoding method that performs bit truncation and prediction on a to-be-encoded block when a forcible bit rate control condition is met, calculating cost values for both methods and selecting the mode with a lower encoding cost to ensure the bit rate is controlled effectively, thereby prioritizing the retention of useful information perceivable by human eyes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If forcible bit rate control is applied when the encoding bit rate reaches the upper limit, then the system memory and bandwidth limitations are met, but the decoded image becomes greatly distorted
Solution Approach 1:
The patent changes the parameter of bit depth for different color components. Specifically, it reduces the bit depth for chroma components (Cb and Cr) while maintaining full bit depth for luma components. This selective parameter change allows the system to reduce overall bit rate while preserving perceptually important information, thereby meeting bit rate constraints without causing significant image distortion.
Solution Approach 2:
The patent applies different encoding quality levels to different parts of the image data. Luma components (brightness information) are encoded with higher precision while chroma components (color information) are encoded with lower precision. This local quality differentiation is based on human visual system characteristics, where brightness perception is more sensitive than color perception, thus maintaining overall image quality while reducing bit rate.
2Productivity
If lossy compression is applied to reduce memory and bandwidth usage, then the compression rate increases, but image quality may be affected
Solution Approach 1:
The patent applies lossy compression selectively to chroma components by reducing their bit depth, while maintaining lossless or higher-quality encoding for luma components. This parameter-based differentiation enables the system to achieve higher compression rates overall while preserving the perceptually critical brightness information, thus improving productivity without significantly degrading image quality.
Solution Approach 2:
The patent implements differential compression where different compression levels are applied to different color components. The luma component receives minimal compression to preserve brightness detail, while the chroma components undergo more aggressive compression since color information is less critical to human perception. This local quality approach achieves high compression rates while maintaining acceptable image quality.
3Quantity of substance
If conventional bit rate control methods are used, then the encoding bit rate is reduced to meet system limitations, but the decoded image becomes greatly distorted
Solution Approach 1:
Instead of uniformly reducing the bit rate across all components, the patent changes the bit depth parameter selectively for chroma components. This intelligent parameter modification allows the system to reduce encoding bit rate to meet system limitations while preserving the quality of perceptually important luma information, thereby maintaining reliability of image decoding quality.
Solution Approach 2:
The patent applies local quality preservation by maintaining high encoding quality for luma components while accepting lower quality for chroma components. This spatial-frequency domain differentiation ensures that the most visually important information remains reliable even when the overall bit rate is constrained by system limitations.
Data Source
AI summary
This application provides example encoding methods and example encoders. One example method includes performing bit truncation on a to-be-encoded block when a bit rate control condition is satisfied. A first cost value corresponding to the bit truncation can then be calculated. The to-be-encoded block can then be predicted to determine a prediction residual of the to-be-encoded block when the bit rate control condition is satisfied. A second cost value corresponding to the prediction can then be calculated based on the prediction residual. The first cost value can then be compared with the second cost value to determine an encoded bit.