RAW Image Compression via Gamma Correction for Dark Pixel Enhancement
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Solution Overview
Problem
RAW images require significant data storage, leading to potential image quality deterioration when compressed, as existing compression techniques do not effectively manage pixel values in dark and high-luminance portions.
Innovation Solution
An image processing apparatus that performs non-linear data conversion to raise pixel values in dark portions and adjust parameters based on image features, ensuring minimal compression error and efficient data storage without degrading image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the RAW image is compressed to suppress data amount, then storage efficiency is improved, but image quality deteriorates
Solution Approach 1:
The patent applies preliminary gamma correction to the RAW image before compression. By adjusting the pixel value distribution in advance (raising dark portions and lowering high-luminance portions), the image is prepared optimally for subsequent compression, ensuring that compression errors have minimal impact on perceived image quality.
Solution Approach 2:
The patent changes the parameter distribution of pixel values through gamma correction. Specifically, it transforms the luminance distribution by applying a gamma function, which redistributes pixel values to concentrate information in regions where the human visual system is most sensitive, thereby reducing the impact of compression artifacts.
2Manufacturing precision
If pixel values in dark portions are raised to improve visibility, then image quality is improved, but compression errors increase
Solution Approach 1:
The patent applies gamma correction with a specific gamma value (typically between 0.45 and 0.55) to transform the luminance distribution. This parameter change raises dark portions while simultaneously lowering high-luminance portions, creating an optimized distribution that balances visibility improvement with compression error minimization.
Solution Approach 2:
The patent converts the potential harm of raising dark portions (which could amplify compression errors) into a benefit by combining it with lowering high-luminance portions. The net effect is that while dark portions are enhanced for visibility, the overall distribution is optimized to reduce the impact of compression artifacts on perceived image quality.
3Loss of information
If high-luminance portions are lowered to reduce compression errors, then compression efficiency is improved, but image quality may deteriorate
Solution Approach 1:
The gamma correction function simultaneously lowers high-luminance portions while raising dark portions. This dual action creates an optimized luminance distribution where the reduction in high-luminance values compensates for potential information loss, maintaining image quality while reducing compression errors.
Solution Approach 2:
The patent applies different transformations to different luminance regions through the gamma function. Dark portions are raised with greater magnitude than high-luminance portions are lowered, creating a non-uniform but optimized distribution that preserves important image information while minimizing compression artifacts.
Data Source
AI summary
An image processing apparatus includes a development processing unit configured to perform development processing for a first RAW image, an output unit configured to output the first RAW image subjected to the development processing, a RAW compression unit configured to compress a second RAW image and generate the second RAW image which remains compressed, and a control unit configured to write the compressed second RAW image into a storage medium, wherein the first RAW image and the second RAW image are respectively images obtained from the same RAW image, and a level of pixels in a dark portion in the second RAW image has been more raised than that in the first RAW image.