Block-Based Image Compression With Adaptive Color Palettes
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Solution Overview
Problem
Existing image compression techniques, particularly lossy algorithms, require significant time and processor power, making them unsuitable for systems with limited resources or needing fast compression.
Innovation Solution
A block-based image compression method that reduces the number of color palette values, using index values and palette averages, which can be implemented in an ASIC, and further compresses palettes by reordering and interpolating in three-dimensional color space, resulting in a simple and fast compression process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If lossy compression algorithms (such as Fast Fourier Transform, Discrete Cosine Transform, or Wavelet Transforms) are used to achieve guaranteed compression ratio, then compression effectiveness is improved, but processor power consumption and computation time increase substantially
Solution Approach 1:
The patent divides the image into multiple blocks and processes each block independently using a simplified compression algorithm. Each block is quantized separately with its own palette, allowing parallel processing and reducing overall computational complexity while maintaining compression effectiveness
Solution Approach 2:
The patent changes the approach from complex transform-based compression to a simplified quantization-based method using color palettes. By modifying the compression parameters to use block-based quantization with limited color palettes, the algorithm achieves compression without requiring substantial processor power
2Loss of information
If complex transform-based lossy compression algorithms are used to achieve guaranteed compression ratio, then compression effectiveness is improved, but compression and decompression time increase
Solution Approach 1:
The patent divides the image into multiple blocks and processes each block independently using a simplified compression algorithm. Each block is quantized separately with its own palette, allowing parallel processing and reducing overall computational complexity while maintaining compression effectiveness
Solution Approach 2:
The patent uses simple quantization tables and color palettes that can be quickly generated and discarded for each block, replacing the need for complex, time-consuming transform operations. This approach sacrifices some compression efficiency for much faster processing
3Ease of operation
If simple fast image compression is used to reduce processor power requirements, then ease of operation is improved, but compression ratio effectiveness deteriorates
Solution Approach 1:
The patent applies different quantization parameters and palette sizes to different blocks based on their local characteristics. This allows the algorithm to achieve better overall compression by adapting to local image variations while maintaining simplicity and low computational requirements
Solution Approach 2:
The patent uses dynamic palette generation and adaptive quantization where the compression parameters are adjusted based on the content of each block. This dynamic adaptation improves compression effectiveness without significantly increasing computational complexity
Data Source
AI summary
In a method of image compression, a processor computes a palette for a block of pixels, the palette having palette values; and the processor computes index values, where some index values map a pixel to a palette value and some index values map a pixel to a value that is between two palette values.