Image Detail Enhancement via Weighted High-Pass Filtering
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Solution Overview
Problem
Current image processing methods face challenges in enhancing details while maintaining a low noise level, especially in low-light conditions, as high edge enhancement often results in a high noise level.
Innovation Solution
An image processing method that calculates an information measure, uses a weighting measure based on this, and applies low-pass filtering to separate detail-enhanced and noise-reduced images by subtracting low-pass filtered images from the original, scaling the high-pass filtered image with the weighting measure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high edge enhancement is applied to improve detail visualization, then image detail quality is improved, but noise level increases
Solution Approach 1:
The image processing method segments the image into multiple layers: a low-pass filtered background layer and a high-pass filtered detail layer. By separating these components and processing them differently, the patent enhances details in the high-pass layer while maintaining noise reduction in the low-pass layer, thus resolving the contradiction between detail enhancement and noise suppression.
Solution Approach 2:
The patent applies different processing qualities to different regions of the image based on local characteristics. The weighting measure adjusts the contribution of detail enhancement locally, allowing strong enhancement in regions with important details while suppressing enhancement in noisy regions, thereby improving detail quality without uniformly increasing noise across the entire image.
2Adaptability or versatility
If image compression is applied to reduce information content, then adaptability to display devices is improved, but image quality deteriorates
Solution Approach 1:
The patent introduces an intermediary processing step that calculates a weighting measure based on local image characteristics before final composition. This intermediary measure acts as a mediator between the compressed background layer and the detail layer, preserving important quality information while adapting to display constraints by selectively enhancing only meaningful details.
Data Source
AI summary
One or more embodiments of the invention relate to an image processing system and method for detail enhancement and noise reduction, in which the method includes: (a) an original image is created, (b) an information measure is calculated on the basis of the original image, (c) a weighting measure is calculated on the basis of the information measure, (d) the original image is low-pass filtered with a low-pass filter to form a low-pass filtered image, (e) a high-pass filtered image is calculated by subtracting the low-pass filtered image from the original image, (f) a detail-enhanced and noise-reduced image is obtained by a high-pass image scaled with the weighting measure being added to the low-pass image. One or more embodiments of the invention additionally relate to an image processing device comprising an image recording device, an image processing unit and an image display unit.