Image Processing Device Fixed-Length Block Compression
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Solution Overview
Problem
Existing image compression methods face challenges in achieving a balance between image quality and compression ratio, particularly at edge portions where data is not redundant, and struggle with random access of compressed data in memory.
Innovation Solution
An image processing device and method that extracts pixel blocks, detects maximum and minimum pixel values, calculates reference values, divides blocks into subblocks, selects a reference value close to pixel distributions, and quantizes absolute difference values to code and decode pixel data efficiently, ensuring consistent bit lengths and high compression ratios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If variable-length compression is used to achieve high compression ratio, then compression efficiency is improved, but random access capability deteriorates
Solution Approach 1:
The image data is divided into multiple blocks, and each block is independently compressed with its own fixed bit length. This segmentation allows the overall data to achieve high compression while maintaining fixed-length structure for random access capability.
Solution Approach 2:
The patent changes the compression parameter from variable-length to fixed-length by controlling the bit length of each block to be equal. This parameter change enables both high compression ratio and random access capability to coexist.
2Ease of operation
If uniform quantization is applied to all blocks, then random access is improved, but image quality deteriorates at edge portions
Solution Approach 1:
The patent applies different quantization characteristics to different blocks based on their content. Blocks with edge portions use finer quantization to maintain image quality, while flat portions use coarser quantization to achieve higher compression, thus resolving the contradiction between random access and image quality.
Solution Approach 2:
The quantization step size is dynamically adjusted for each block based on its characteristics (edge or flat portion). This dynamic adaptation allows the system to maintain both random access capability through fixed bit length and high image quality through localized quantization optimization.
3Productivity
If compression is controlled on a process-by-process basis, then compression efficiency is improved, but device complexity increases
Solution Approach 1:
The compression process is segmented into independent block-level operations. Each block is processed separately with fixed bit length control, which simplifies the overall processing logic while maintaining high compression efficiency through parallelizable independent operations.
Data Source
AI summary
An image processing device includes a processor configured to: extract pixel blocks; detect pixels having a maximum value and a minimum value in each of the pixel blocks; calculate reference value candidates from the maximum and the minimum values; calculate an absolute difference value relative to each of the maximum value, the minimum value, and the reference value candidates; divide each of the pixel blocks into subblocks; select, as a reference value from among the reference value candidates in each of the subblocks, a reference value candidate close to the pixel values in which the pixels included in each of the subblocks are distributed; extract a closest difference value, the minimum value, and the reference value; quantize each of the closest difference values into a quantization value by using the difference value that is the largest from among the closest difference values; and code the quantization value.