Image Processing Noise Reduction via Edge-Aware Frequency Band Compositing
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Solution Overview
Problem
Existing noise reduction methods in image processing often blur edges and textures with low contrast, as they are not accurately detected and treated, leading to undesirable composite ratios between high-resolution and low-resolution images.
Innovation Solution
An image processing apparatus that divides images into frequency bands and uses specific units to detect edges and low-contrast edges, applying weighted compositing to preserve sharpness in edge regions and reduce noise in smooth portions by calculating composite ratios and correction values based on edge detection and local variance analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional edge detection methods are used to composite high-resolution and low-resolution images, then high-contrast edges are preserved, but low-contrast edges and textures are blurred due to inaccurate detection
Solution Approach 1:
The patent segments the image processing into multiple frequency bands using Laplacian pyramids, separating high-frequency components (edges, textures) from low-frequency components (smooth regions). This allows different processing strategies to be applied to different frequency components, improving both detection accuracy and preserving image sharpness simultaneously.
Solution Approach 2:
The patent applies local quality by using adaptive composite ratios that vary spatially across the image. The composite ratio is dynamically adjusted based on local edge detection results and variance calculations, allowing high-contrast edges to be preserved with high composite ratios while low-contrast regions receive appropriate noise reduction with lower composite ratios, thus maintaining local image quality.
2Object-affected harmful factors
If noise reduction processing is applied to smooth regions, then noise is reduced, but edges and textures may be blurred if not properly detected
Solution Approach 1:
The patent changes parameters by calculating variance in different regions to dynamically adjust the composite ratio. Regions with low variance (smooth regions) receive higher noise reduction with lower composite ratios, while regions with high variance (edge regions) maintain higher composite ratios to preserve sharpness. This parameter adaptation allows simultaneous noise reduction and edge preservation.
3Manufacturing precision
If high composite ratio is used for edge regions, then edge sharpness is maintained, but noise reduction effectiveness is reduced
Solution Approach 1:
By segmenting the image into different frequency bands using Laplacian pyramids, the patent can apply different composite ratios to different frequency components. High-frequency components (edges) use higher composite ratios to preserve sharpness, while low-frequency components (smooth regions) use lower composite ratios to maximize noise reduction, thus resolving the contradiction between sharpness and noise reduction.
Data Source
AI summary
An image processing apparatus configured to divide an image into frequency bands and reduce noise, in which a first image includes a high-band frequency component, and a second image includes a low-band frequency component, includes: a first detecting unit configured to detect an edge in at least one of the first image and the second image; a second detecting unit configured to detect a low-contrast edge that is of a lower contrast than a contrast of the edge detected by the first detecting unit in the at least one of the first image and the second image; a compositing unit configured to composite the first image and the second image using a weighting corresponding to the edge and the low-contrast edge.