Image Compression Circuit Selecting Block Results via Thresholds
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Solution Overview
Problem
Existing image data compression methods for LCD panels face a trade-off between storage capacity and display quality, where lower compression ratios require larger storage but higher ratios degrade image quality, and there is a need for an approach that balances these factors.
Innovation Solution
An image data compression apparatus and method that applies multiple compression approaches to a block, derives characteristic values from the results, and selects a target compression result based on at least one characteristic value threshold to ensure adequate storage while minimizing display quality degradation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a higher compression ratio is employed to reduce storage requirements, then the storage capacity requirement is reduced, but the difference between original and recovered image data becomes more significant, leading to degradation of display quality
Solution Approach 1:
The system dynamically selects compression ratios based on the complexity of image blocks. Different blocks within the same frame are processed with different compression levels, allowing the system to adapt the compression ratio to the local content characteristics. This resolves the contradiction by applying higher compression to simple blocks (reducing storage) while using lower compression for complex blocks (maintaining quality).
Solution Approach 2:
The invention divides the image into blocks and applies different compression approaches to different blocks based on their characteristics. Some blocks use higher compression ratios while others use lower compression ratios, allowing each block to be compressed to the optimal level for its specific content, thereby balancing storage requirements with display quality globally.
2Manufacturing precision
If a lower compression ratio is employed to maintain display quality, then the difference between original and recovered image data is minimized, but the frame buffer requires greater storage capacity
Solution Approach 1:
The system dynamically adjusts the compression ratio for each block based on its complexity. Simple blocks are compressed more aggressively to save storage space, while complex blocks are compressed less to maintain quality. This dynamic adaptation allows the system to achieve both low storage requirements and high display quality simultaneously.
Solution Approach 2:
Different blocks are processed with different compression ratios according to their local characteristics. This local differentiation enables the system to minimize storage usage for simple regions while preserving quality for complex regions, thereby resolving the contradiction between storage capacity and display quality.
3Adaptability or versatility
If multiple compression approaches are applied to generate candidate compression results, then the ability to select optimal compression result is improved, but the processing complexity increases
Solution Approach 1:
The image is divided into blocks, and for each block, a limited number of compression approaches are applied to generate candidate results. This segmentation allows the system to manage complexity by processing blocks independently and using a manageable number of compression methods per block rather than applying all possible methods to the entire image.
Solution Approach 2:
Instead of exhaustively trying all possible compression approaches, the system applies a partial set of compression methods to each block and selects from those candidates. This partial action reduces processing complexity while still providing sufficient adaptability to achieve optimal compression results.
Data Source
AI summary
An exemplary image data compression apparatus includes a compression circuit, a characteristic value extracting circuit, and a selecting circuit. The compression circuit is utilized for applying a plurality of different compression approaches to a first block, and accordingly generating a plurality of first candidate compression results of the first block. The characteristic value extracting circuit is coupled to the compression circuit, and utilized for deriving a plurality of first characteristic values from the first candidate compression results, respectively. The selecting circuit is coupled to the compression circuit and the characteristic value extracting circuit, and utilized for selecting a target compression result of the first block from the first candidate compression results according to the first characteristic values and at least one characteristic value threshold.