Color Image Data Compression Using Cell-Based Thresholding
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Solution Overview
Problem
Existing color image data compression techniques for printing devices often fail to effectively compress high-definition graphics while maintaining image quality, requiring extensive computational resources and resulting in poor compression of RGB data.
Innovation Solution
A method that determines the number of colors in a cell of an image, applying lossy or lossless compression based on predetermined thresholds, reducing colors by averaging similar pixels, and using specific encoding schemes for RGB data streams, including run-length encoding, to achieve efficient compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image compression techniques preserve too many details, then image quality is maintained, but data transfer requirements increase and computation resources are extensively required
Solution Approach 1:
The patent applies different compression strategies to different regions of the image based on local characteristics. Graphics regions with sharp edges and high contrast are compressed differently from photographic regions, allowing optimal compression ratios while maintaining visual quality in each specific area.
Solution Approach 2:
The patent dynamically adjusts compression parameters such as quantization levels, block sizes, and transformation types based on the local image content. This allows the system to achieve better compression ratios in suitable regions while preserving critical visual information in regions where it matters most.
2Measurement precision
If image compression techniques preserve too many details, then image quality is maintained, but computation resources are extensively required
Solution Approach 1:
The patent identifies and processes different image regions with appropriate algorithms, applying computationally intensive techniques only where necessary for quality preservation while using simpler methods in other areas, thus reducing overall computational burden.
Solution Approach 2:
The patent applies compression techniques at varying levels of aggressiveness depending on the region, using full computational power only where needed to maintain quality, and accepting higher compression in regions where visual quality is less critical.
3Adaptability or versatility
If a general purpose compression technique is used for printing devices, then both graphics and images can be compressed, but compression efficiency may be reduced compared to specialized techniques
Solution Approach 1:
The patent implements a unified compression framework that can handle both graphics and photographic images through a single system, eliminating the need for separate specialized compressors while maintaining good performance for both types of content.
Solution Approach 2:
The patent automatically segments the image into different regions (graphics vs. photographic) and applies appropriate compression strategies to each segment, allowing a general-purpose system to achieve specialized-level efficiency for different content types.
Data Source
AI summary
Color image data is compressed by determining the number of colors within a cell of an input image, each cell comprising an N×M array of pixels; in response to determining that the number of colors is greater than a first predetermined threshold, compress the cell using lossy compression; and in response to determining that the number of colors is less than the first predetermined threshold, reduce the number of colors.