Asymmetric PSF Unsharp Mask for Optical Aberration Correction
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Solution Overview
Problem
Conventional image sharpening methods, such as those using rotationally symmetric unsharp masks, struggle to effectively correct asymmetrical aberrations and blurs in images due to the intricately shaped influence of point spread functions (PSF) in optical systems, leading to undershoot or insufficient correction, and require increased processing load and storage capacity.
Innovation Solution
The use of a point spread function (PSF) as an unsharp mask that approximates a rotationally asymmetric distribution, allowing for more accurate correction by varying the correction amount based on image-pickup conditions, such as focal length and aperture, and generating coefficient data to reduce storage requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a rotationally symmetric filter is employed as an unsharp mask, then the processing is simple and storage requirements are low, but it cannot effectively correct asymmetric aberrations and causes undershoot or insufficient correction
Solution Approach 1:
The patent applies asymmetry by using a point spread function (PSF) that exhibits rotational asymmetry to construct the unsharp mask filter. This asymmetric PSF-based filter is designed to match the asymmetric characteristics of optical aberrations in the imaging system, enabling effective correction of asymmetric blurring while avoiding the undershoot problems associated with symmetric filters. The asymmetric filter coefficients are derived from the asymmetric PSF through Fourier transformation, allowing the filter to adapt to the specific asymmetric aberration patterns of the optical system.
2Manufacturing precision
If an asymmetric PSF-based unsharp mask is used to correct asymmetric aberrations, then correction accuracy improves, but processing load and storage requirements increase
Solution Approach 1:
The patent implements preliminary action by pre-calculating and storing the point spread function (PSF) characteristics and the corresponding asymmetric filter coefficients in a lookup table or memory structure. During actual image processing, the system retrieves the pre-computed PSF and filter coefficients based on the current imaging conditions (such as aperture settings and focal length), avoiding the need to perform complex Fourier transformations in real-time. This pre-computation approach significantly reduces the processing load during image sharpening operations while maintaining high correction accuracy.
3Productivity
If conventional unsharp mask processing is applied, then processing speed is maintained, but the sharpening effect is insufficient for asymmetric blurs
Solution Approach 1:
The patent applies local quality by using a point spread function (PSF) that varies according to the local imaging conditions and position within the image field. The asymmetric PSF is calculated or selected based on specific imaging parameters such as aperture size, focal length, and object distance, allowing the unsharp mask filter to be locally adapted to the actual blur characteristics at different regions of the image. This localized approach ensures that the sharpening operation is optimized for the specific asymmetric blur patterns present in each region, rather than applying a uniform symmetric filter across the entire image.
Data Source
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AI summary
An image processing program that causes a computer to execute an image processing method comprising acquiring step (S11) of acquiring an input image generated by image pickup through an optical system, generating step (S13) of generating a point spread function by using coefficient data of a function approximating a point spread function corresponding to an image-pickup condition of the optical system, and providing step (S15) of providing unsharp mask processing to the input image using a filter generated based on information of the point spread function generated by using the coefficient data. The filter is a filter having two-dimensional data.