Image Processing Apparatus Resolution Enhancement Flat Region Noise
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Solution Overview
Problem
Existing image processing methods for enhancing low-resolution images can deteriorate the quality of high-resolution images due to incorrect pixel value modifications and noise amplification in flat areas.
Innovation Solution
An image processing apparatus that calculates estimated pixel values for a provisional high-resolution image through interpolation, segments the image into edge, texture, and flat regions, and adjusts pixel values based on fractional pixel accuracy to minimize errors and avoid noise amplification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pixel values are modified using multi-frame deterioration inverse conversion method, then resolution enhancement is achieved, but image quality deteriorates due to wrong corresponding positions and noise amplification
Solution Approach 1:
The patent applies different processing strategies to different image regions by segmenting the image into flat regions and non-flat regions. For flat regions, corresponding position calculation is omitted to avoid noise amplification, while for non-flat regions, the full multi-frame deterioration inverse conversion process is applied to achieve resolution enhancement. This local differentiation resolves the contradiction by preventing quality deterioration in flat regions while maintaining resolution enhancement in regions where it is beneficial.
2Measurement precision
If corresponding position calculation is performed for all pixels, then resolution enhancement is improved, but noise component in flat areas is amplified
Solution Approach 1:
The patent segments the image into flat regions and non-flat regions based on gradient calculation. This segmentation allows the system to apply corresponding position calculation only to non-flat regions where it provides resolution enhancement, while excluding flat regions where it would amplify noise. The segmentation process uses gradient magnitude thresholds to identify flat regions, enabling selective application of the resolution enhancement algorithm.
3Reliability
If image is segmented into different regions, then noise amplification is reduced, but processing complexity increases
Solution Approach 1:
The patent changes the processing parameters (whether to calculate corresponding positions) based on the region type identified through segmentation. For flat regions, the parameter is set to skip corresponding position calculation, while for non-flat regions, the parameter is set to perform the calculation. This parameter-based control strategy manages processing complexity by avoiding unnecessary calculations in flat regions while maintaining image quality through selective processing.
Data Source
AI summary
An image processing apparatus calculates estimated pixel values of respective pixels of a provisional high-resolution image by interpolation on basis of pixel values in a reference frame. Interior of the reference frame is segmentalized into an edge region, a texture region or a flat region and others on a basis of pixel values of respective pixels. The respective pixels in the reference frame are set as target pixels one by one in sequence. Corresponding positions on the provisional high-resolution image are calculated, of the respective target pixels in decimal accuracy on a basis of information on the segmented regions including the target values. The estimated pixel values are modified so that differences from the pixel values of the target pixels to provisionally estimated pixel values obtained from the estimated pixel values of the provisional high-resolution image for pixels around the corresponding positions of the target pixels, becomes smaller. Modified pixel values and then obtained.