Multi-Resolution Image Processing for Contrast Enhancement
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Solution Overview
Problem
Existing image processing methods struggle to effectively enhance images with varying contrast levels, as they often fail to appropriately adjust pixel values across different resolution levels, leading to inadequate detail enhancement in both high and low frequency regions.
Innovation Solution
An image processing apparatus and method that involves obtaining image data, generating multiple levels of pixel values through smoothing and resolution conversion, correcting pixel values based on differences between original and smoothed data, and utilizing high frequency components to enhance image data at each resolution level, thereby improving contrast and detail across varying contrast levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If unsharp mask processing is performed in two different frequency regions to locally enhance contrast, then contrast enhancement is achieved, but the method fails to appropriately handle images with varying contrast levels across different resolution levels
Solution Approach 1:
The image processing is segmented into multiple resolution levels (first level, second level, etc.), where each level undergoes independent smoothing and contrast enhancement processing. This allows different regions of the image spectrum to be handled with appropriate processing strength, resolving the contradiction between precision and adaptability.
Solution Approach 2:
The invention adds a resolution level dimension to the processing approach, transforming the single-frequency-region unsharp mask into a multi-resolution processing system. By operating across multiple scales, the system achieves both precise local contrast enhancement and adaptability to varying contrast levels throughout the image.
2Manufacturing precision
If pixel values are smoothed and resolution converted repeatedly to generate multiple levels, then detail enhancement capability is improved, but processing complexity increases
Solution Approach 1:
The image data is pre-processed by generating all necessary smoothed versions at different resolution levels before the contrast enhancement step. This preliminary preparation allows the subsequent enhancement phase to operate efficiently on pre-computed data, reducing overall processing complexity while maintaining high detail enhancement precision.
3Manufacturing precision
If correction is applied to pixel values based on differences between original and smoothed data, then image quality is enhanced, but processing time increases
Solution Approach 1:
The correction operation is applied selectively and efficiently by computing only the necessary differences between original and smoothed pixel values at each resolution level. This partial action approach achieves high image quality precision without requiring exhaustive processing of all possible pixel combinations, thus reducing processing time.
Data Source
AI summary
An image processing apparatus, including a first obtaining unit which obtains image data; a first generation unit which generates a plurality of levels of pixel values that are respectively smoothed in a plurality of levels of resolutions; a correction unit which corrects the pixel value of the obtained image data for each of the levels; and a control unit which controls so as to form image data in which the pixel value of the obtained image data is enhanced by utilizing a high frequency component in each of the levels of the image data having the pixel value corrected by the correction unit, the high frequency component corresponding to each of the levels of the resolutions.