Adaptive Image Compression Circuit for Display Drivers
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Solution Overview
Problem
Existing image compression methods for display panels in mobile devices face issues with block noise and granular noise, particularly when dealing with varying pixel correlations, leading to increased memory requirements and power consumption.
Innovation Solution
A display panel driver with a compression circuit that selects among multiple compression methods based on pixel correlation, using techniques like representative value calculation and bit plane reduction to generate compressed image data, reducing noise and memory usage while maintaining constant bit numbers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If image data is compressed using block coding methods, then memory capacity is reduced, but block noise is generated due to differences in correlation between adjacent blocks
Solution Approach 1:
The patent applies local quality by differentiating compression processing between blocks with high correlation and blocks with low correlation. Specifically, blocks with high pixel correlation undergo representative value compression (reducing memory usage), while blocks with low correlation are processed differently to avoid block noise. This localized approach allows the system to optimize memory capacity for suitable blocks without generating harmful block noise artifacts across the entire image.
Solution Approach 2:
The patent implements dynamic compression method selection based on the correlation characteristics of each block. The system dynamically determines whether to apply representative value compression or alternative processing methods by evaluating pixel correlation metrics for each block. This dynamic adaptation allows the compression strategy to change locally based on image content, resolving the contradiction between memory reduction and noise prevention.
2Use of energy by moving object
If image data is compressed to reduce memory capacity, then power consumption is reduced, but image quality deteriorates due to noise
Solution Approach 1:
The patent applies local quality by differentiating compression processing between blocks with high correlation and blocks with low correlation. Specifically, blocks with high pixel correlation undergo representative value compression (reducing memory usage), while blocks with low correlation are processed differently to avoid block noise. This localized approach allows the system to optimize memory capacity for suitable blocks without generating harmful block noise artifacts across the entire image.
Solution Approach 2:
The patent implements dynamic compression method selection based on the correlation characteristics of each block. The system dynamically determines whether to apply representative value compression or alternative processing methods by evaluating pixel correlation metrics for each block. This dynamic adaptation allows the compression strategy to change locally based on image content, resolving the contradiction between memory reduction and noise prevention.
3Reliability
If multiple compression methods are implemented to handle different pixel correlations, then image quality is maintained, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the image into blocks and further segmenting the compression processing into different pathways based on correlation characteristics. The compression circuit is segmented into correlation evaluation units, representative value compression units, and alternative processing units. This modular segmentation allows multiple compression methods to be implemented in a structured way, managing complexity through clear functional division while maintaining image quality through appropriate method selection.
4Quantity of substance
If representative value compression is applied to all blocks, then memory capacity is minimized, but block noise increases significantly
Solution Approach 1:
The patent applies local quality by differentiating compression processing between blocks with high correlation and blocks with low correlation. Specifically, blocks with high pixel correlation undergo representative value compression (reducing memory usage), while blocks with low correlation are processed differently to avoid block noise. This localized approach allows the system to optimize memory capacity for suitable blocks without generating harmful block noise artifacts across the entire image.
Solution Approach 2:
The patent implements dynamic compression method selection based on the correlation characteristics of each block. The system dynamically determines whether to apply representative value compression or alternative processing methods by evaluating pixel correlation metrics for each block. This dynamic adaptation allows the compression strategy to change locally based on image content, resolving the contradiction between memory reduction and noise prevention.
Data Source
AI summary
A circuit includes an image decompression circuit configured to receive compressed image data which are generated by compressing image data of a set of pixels of a target block by using a selected compression method selected from a plurality of compression methods based on a correlation among said image data of said set of pixels of said target block, and to generate decompressed image data by decompressing said compressed image data by using a decompression method corresponding to said selected compression method.