Image Compression via Device-Specific Parameter Catalogues
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Solution Overview
Problem
Current image compression algorithms fail to optimize results across various conditions, as they often require manual tuning and do not account for the specific hardware used to acquire the image, leading to suboptimal file size and quality compromises.
Innovation Solution
The method involves creating a compression parameter catalogue that identifies the image acquisition device and its settings, allowing for the automatic selection of optimal compression algorithms and parameters based on predefined tables, ensuring quantifiable information loss and improved compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If general image compression algorithms are used, then file size is reduced, but image quality deteriorates due to suboptimal compression parameters
Solution Approach 1:
The patent applies parameter changes by adjusting compression algorithm parameters based on image acquisition device characteristics. The system identifies the specific camera or sensor used to capture the image and selects compression parameters optimized for that device's sensor type, color filter array, and processing pipeline, thereby improving image quality while maintaining file size reduction.
Solution Approach 2:
The patent segments the compression process by first identifying the image acquisition device characteristics, then selecting appropriate compression algorithms and parameters based on those characteristics. This segmentation allows different compression strategies to be applied to images from different devices, resolving the contradiction between file size and quality.
2Manufacturing precision
If manual tuning of compression algorithms is performed, then image quality is improved, but operational complexity increases
Solution Approach 1:
The patent implements self-service by enabling the compression system to automatically identify image acquisition device characteristics and select optimal compression parameters without manual intervention. The system autonomously queries device information, matches it with appropriate compression algorithms, and applies the correct parameters, thereby maintaining high image quality while eliminating manual tuning complexity.
Solution Approach 2:
The patent uses feedback by utilizing metadata and characteristics from the image acquisition device to inform the selection of compression parameters. The system receives feedback about the device type, sensor characteristics, and processing pipeline, then uses this information to automatically adjust compression settings, resolving the contradiction between quality and operational ease.
3Productivity
If compression algorithms are specialized for specific conditions, then compression efficiency is improved, but adaptability decreases
Solution Approach 1:
The patent achieves universality by creating a compression system that can handle multiple image acquisition device types through a unified framework. The system identifies the specific device characteristics and selects from multiple specialized compression algorithms, making the overall system adaptable to various conditions while maintaining the efficiency benefits of specialized algorithms for each device type.
Data Source
AI summary
A system and method to compress image data by first identifying the device and settings with which the image data was generated, and then optimizing the compression accordingly. A catalogue that associates imaging devices and settings to compression parameters is generated, so that when an image needs to be compressed, the system will identify the device and settings and extract compression parameters from the catalogue. These parameters are used during compression to achieve higher compression performance and optionally to normalize the compressed data as to make it more homogenous for further processing.