Image Processing System Adaptive Wavelet PCM Coding
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Solution Overview
Problem
Existing data compression methods for video streaming are inefficient, particularly in wireless networks, leading to high bandwidth demands and increased costs, as they fail to achieve optimal compression ratios and quality, especially for on-demand video content.
Innovation Solution
An image processing system that transforms input image blocks into wavelet coefficients, organizes them into bitplanes with priority values, and uses a scaling factor to generate a scaled wavelet block, determining whether to apply lossy compression using wavelet coding or PCM mode based on compression ratio thresholds, thereby optimizing compression and reducing bandwidth requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If wavelet coding is used for compression, then compression ratio is improved, but quality degradation occurs due to lossy compression
Solution Approach 1:
The system dynamically switches between wavelet coding mode and PCM mode based on real-time compression ratio evaluation. When wavelet coding achieves sufficient compression ratio, it is used; when compression ratio is insufficient, the system switches to PCM mode to maintain quality, making the coding strategy adaptive and dynamic rather than fixed
Solution Approach 2:
The system changes the coding parameter (coding mode) based on compression ratio performance. By monitoring the compression ratio and switching between different coding methods (wavelet vs PCM), the system adjusts parameters to optimize both compression efficiency and quality preservation
2Loss of energy
If existing compression codecs are used, then bandwidth is reduced, but compression efficiency is insufficient for wireless networks
Solution Approach 1:
The system implements feedback by evaluating the actual compression ratio achieved and using this information to determine whether to switch coding modes. This closed-loop feedback mechanism ensures the system continuously optimizes compression efficiency based on real performance data, adapting to varying network conditions
Solution Approach 2:
The coding strategy is made dynamic by switching between different compression methods based on real-time compression ratio measurement, allowing the system to adapt to changing network conditions and optimize bandwidth usage efficiency
3Quantity of substance
If higher compression is applied, then bandwidth requirements are reduced, but error rate increases
Solution Approach 1:
The system dynamically adjusts the compression level by switching between wavelet coding and PCM mode based on the balance between compression ratio and error rate. This dynamic adaptation allows optimization of bandwidth usage while maintaining acceptable error rates through intelligent mode selection
Data Source
AI summary
An image processing system, and a method of operation thereof, including: a capture device for obtaining an input image block; and an image signal processing hardware coupled to the capture device, the image signal processing hardware including: a coding module including: a scaling correction module for generating a scaled wavelet block based on the input image block, a grey block detection module for determining the input image block to be a grey image block, a compression ratio module for determining the compression ratio of the input image block, a mode setting module for setting a PCM mode identifier based on the compression ratio, the coding module for generating a compressed image block by scanning and coding the input image block using PCM mode; and a decoding module for generating an output image block by decoding the compressed image block for display on a display device.