Intraframe Video Compression With Fixed Bit Rate and Low Distortion
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Solution Overview
Problem
Existing video compression techniques face challenges in achieving high-quality fixed bit rate compression, particularly in intraframe-only compression, where image quality is affected by quantization and bit depth variations, leading to inefficiencies in storage and playback of motion video data.
Innovation Solution
The method employs rate-distortion optimization by transforming image portions into frequency domain coefficients, determining a bit rate for each portion using scale factors, selecting a quantization matrix to minimize distortion, and applying variable length encoding to achieve a desired bit rate, while accommodating multiple bit depths through weighting factors and controlling noise with a variable deadzone.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If intraframe compression with quantization is used to reduce storage requirements, then storage efficiency is improved, but image quality deteriorates due to information loss
Solution Approach 1:
The patent applies rate-distortion optimization by dynamically adjusting quantization parameters (scale factors) for different frequency coefficients. By changing these parameters, the system optimizes the balance between compression ratio and image quality, reducing information loss while meeting storage requirements.
Solution Approach 2:
The patent implements different quantization strength for different frequency components of the image. Important frequency components retain more detail while less important ones are compressed more aggressively, achieving local optimization of quality versus compression.
2Quantity of substance
If stronger quantization is applied to achieve higher compression ratios, then storage efficiency is improved, but manufacturing precision deteriorates due to increased distortion
Solution Approach 1:
The system uses rate-distortion optimization to select quantization parameters that minimize distortion for a given compression target. By carefully controlling the quantization step sizes, the patent achieves high compression while limiting the increase in image distortion.
3Loss of information
If rate-distortion optimization is implemented to minimize distortion at fixed bit rate, then image quality is improved, but device complexity increases due to additional computational operations
Solution Approach 1:
The patent divides the image into frequency components through discrete cosine transform, allowing independent optimization of each component's quantization. This segmentation enables efficient rate-distortion optimization without requiring exhaustive search of all possible quantization parameters.
Solution Approach 2:
The system performs discrete cosine transform and organizes coefficients in zig-zag order before quantization, preparing the data in advance to facilitate efficient rate-distortion optimization and entropy encoding operations.
4Quantity of substance
If discrete cosine transform and quantization are used for compression, then storage efficiency is improved, but loss of information increases due to quantization errors
Solution Approach 1:
The patent dynamically adjusts quantization scale factors based on rate-distortion optimization, changing the quantization parameters to minimize information loss while achieving the desired compression ratio. This adaptive approach reduces quantization error compared to fixed quantization schemes.
Data Source
AI summary
High quality intraframe-only compression of video can be achieved using rate distortion optimization and without resizing or bit depth modification. The compression process involves transforming portions of the image to generate frequency domain coefficients for each portion. A bit rate for each transformed portion using a plurality of scale factors is determined. Distortion for each portion is estimated according to the plurality of scale factors. A scale factor is selected for each portion to minimize the total distortion in the image to achieve a desired bit rate. A quantization matrix is selected according to the desired bit rate. The frequency domain coefficients for each portion are quantized using the selected plurality of quantizers as scaled by the selected scale factor for the portion. The quantized frequency domain coefficients are encoded using a variable length encoding to provide compressed data for each of the defined portions. The compressed data is output for each of the defined portions to provide a compressed bitstream at the desired bit rate.