Lucy-Richardson Deblurring with Edge Masking to Reduce Ringing
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Solution Overview
Problem
Existing deblurring methods, such as the Lucy-Richardson deconvolution method, often produce ringing artifacts around the edges and borders of reconstructed images, resulting in unsatisfactory image quality.
Innovation Solution
A method that involves creating an edge mask, extending it, forming an initial array, and performing Lucy-Richardson iterations with masking, while also padding the image to prevent artificial edges, and cropping the extended image to match the original size, significantly reduces ringing artifacts around edges and borders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If Lucy-Richardson deconvolution method is used to reduce blurring, then image sharpness is improved, but ringing artifacts appear around edges and borders
Solution Approach 1:
The patent applies preliminary action by creating an edge mask before performing Lucy-Richardson iterations. The edge mask is generated by detecting edges in the blurred image and dilating the edge regions, then inverting to create a mask that protects edge areas during deconvolution. This preliminary preparation prevents ringing artifacts from forming at edges while allowing effective deblurring in non-edge regions.
Solution Approach 2:
The patent implements local quality by applying different processing characteristics to different regions of the image. The edge mask creates distinct treatment zones: edge regions are protected from aggressive deconvolution to prevent ringing, while non-edge regions undergo full Lucy-Richardson processing to maximize sharpness recovery. This localized approach allows each region to be processed according to its specific characteristics.
2Manufacturing precision
If standard Lucy-Richardson iterations are performed, then blurring is reduced, but image quality deteriorates due to ringing artifacts at boundaries
Solution Approach 1:
The patent introduces an intermediary element - the edge mask - that mediates between the deconvolution process and the image data. The mask acts as a selective gate, allowing deconvolution to proceed in safe regions while blocking or attenuating the process in edge regions where ringing would occur. This intermediary protects image quality while preserving blurring reduction benefits.
Data Source
AI summary
A method for reducing blurring in a blurred image (14) of a scene (12) includes the steps of: (i) creating an edge mask (362) from the blurred image (14); (ii) extending the edge mask (362; (iii) forming an initial array (e.g. extending the blurred image (360); and (iv) performing Lucy-Richardson iterations, with masking. With the deblurring method disclosed herein, the reconstructed adjusted image (16) (i) does not have (or has significantly less) ringing artifacts around the edges (22) of the captured object(s) (20C), and (ii) does not have (or has significantly less) ringing artifacts around border (24). As a result thereof, the adjusted image (16) is more attractive and more accurately represents the scene (12).