Image Data Compression Control Points for Bandwidth Optimization
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Solution Overview
Problem
In bandwidth-constrained wireless transmission of image data, existing compression techniques fail to optimize local compression ratios effectively, leading to inefficiencies in data transmission, particularly when the domain of image brightness and color spectrum values evolves.
Innovation Solution
The method involves setting and adjusting control points to specify compression ratios for image data, ensuring that the slope of compression ratios does not exceed 1, thereby optimizing local compression while maintaining overall compression efficiency and preserving bandwidth. This is achieved by scaling and rescaling control points based on minimum and maximum uncompressed values, ensuring that the compression ratios remain within optimal limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If compression ratios are increased to reduce data size for bandwidth-constrained transmission, then transmission efficiency improves, but local compression loss increases and may exceed optimal limits
Solution Approach 1:
The patent applies local quality by dividing the compression domain into multiple regions, each with its own control points specifying different compression ratios. This allows critical regions to maintain lower compression (less loss) while non-critical regions accept higher compression, optimizing the overall trade-off between transmission efficiency and information preservation
Solution Approach 2:
The patent implements dynamic adjustment of control points based on the actual minimum and maximum values in the current image data. The control points are rescaled and repositioned adaptively for each image or video frame, allowing the compression strategy to dynamically respond to changing data characteristics and maintain optimal performance
2Device complexity
If fixed compression ratios are applied to simplify the compression process, then device complexity reduces, but adaptability to evolving data domains deteriorates
Solution Approach 1:
The patent uses preliminary action by pre-defining a set of control points that specify compression ratios for different regions of the compression domain. These control points are established in advance but can be rescaled and repositioned adaptively for each image or video frame, providing a balance between having a structured approach and adapting to changing data characteristics
Solution Approach 2:
The patent applies parameter changes by modifying the positions and values of control points based on the actual minimum and maximum values in the current data. This allows the compression system to adapt to evolving data domains by changing the parameters (control point locations and compression ratios) rather than using fixed values, maintaining effectiveness without requiring complete redesign
Data Source
AI summary
Techniques to provide compression and/or decompression. A method includes obtaining a first set of control points specifying a first set of compression ratios corresponding to respective first regions of a compression domain, and minimum and maximum uncompressed values within the compression domain. The method can further include scaling the first set of control points based on the minimum and maximum uncompressed values to obtain a scaled set of control points, wherein a first scaled control point is located at the minimum uncompressed value, and a last scaled control point is located at the maximum uncompressed value. The method can further include adjusting at least one scaled control point such that a first slope does not exceed 1. The method can further include compressing or decompressing between the compression domain and a range of compressed values, wherein a respective compression ratio corresponds to a respective slope of the set of slopes.