Asymmetric Unsharp Mask for Optical Aberration Correction
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Solution Overview
Problem
Conventional unsharp mask processing struggles to effectively sharpen images deteriorated by complex optical system aberrations, such as asymmetric aberration and sagittal halo, due to its reliance on rotationally symmetric filters, which fail to accurately correct asymmetry and result in insufficient sharpening.
Innovation Solution
An image processing method and apparatus that reconstructs the point spread function (PSF) of the optical system using coefficient data, allowing for variable discretization intervals based on image height, and employs a rotationally asymmetric unsharp mask for more accurate sharpening, utilizing the PSF as the unsharp mask to correct image blurs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a rotationally symmetric filter is used for unsharp mask processing, then the processing is simple and easy to implement, but it cannot effectively correct asymmetric aberrations and sagittal halo, resulting in insufficient sharpening
Solution Approach 1:
The patent applies asymmetry by using an asymmetric filter kernel for the unsharp mask processing. Instead of a rotationally symmetric filter, the filter is designed with different weights in different directions to match the asymmetric point spread function of the optical system, enabling effective correction of asymmetric aberrations and sagittal halo while maintaining computational feasibility
Solution Approach 2:
The patent implements local quality by adapting the filter characteristics to different regions of the image. The unsharp mask processing uses a filter that is tailored to the local point spread function characteristics, allowing different parts of the image to be sharpened with appropriate filter parameters that match their specific aberration patterns
2Device complexity
If the discretization interval of the point spread function is uniform, then the calculation is simple, but it cannot accurately represent the PSF characteristics across different image heights
Solution Approach 1:
The patent applies dynamics by making the discretization interval variable rather than fixed. The interval between sampling points in the point spread function reconstruction is adjusted dynamically based on the image height, with finer intervals near the optical axis and coarser intervals at the periphery, matching the actual variation of optical aberrations across the field of view
Data Source
AI summary
An image processing apparatus includes an acquirer configured to acquire a captured image generated through imaging by an optical system, a reconstruction processor configured to reconstruct a discretized point spread function of the optical system using coefficient data used to approximate the point spread function, and a sharpening processor configured to perform unsharp mask processing for the captured image based on information on the reconstructed point spread function. A discretization interval of the reconstructed point spread function is different according to an image height.