A Phase-difference Wavefront Detection and Image Restoration Method Based on Stack Scanning

Abstract

The invention relates to a laminated scanning based phase-difference wavefront detection and image restoration method which can be used for restoring wavefront distortions and capable of effectively restoring blurred images affected by aberrations. According to the method, a small-aperture diaphragm is moved within a pupil plane of an imaging system in a laminated scanning mode, and corresponding sub-images affected by different aberrations are recorded by using an image sensor. The recorded series of sub-images are processed by using the laminated scanning based phase-difference wavefront detection and image restoration method, and wavefront distortions of the system can be detected and the images can be restored. The method adopts the small-aperture diaphragm to perform space scanning so as to produce the sub-images having phase differences. Compared with various existing technologies for phase difference methods, the Nyquist sampling frequency is more easily met, an aberration detection range is large, out-of-focus light paths and various diffraction devices are not needed, and the laminated scanning based phase-difference wavefront detection and image restoration method has the advantages of being compact in system, convenient to use and the like.

Description

technical field [0001] The invention relates to the technical field of wavefront detection and image restoration, in particular to a phase difference wavefront detection and image restoration method based on stack scanning. Background technique [0002] The phase difference method was first proposed by Gonsalves RA. By adding the known defocus aberration in the wavefront to be measured, according to the obtained focal plane light intensity distribution and multiple light intensity distributions located on different defocus planes, based on the least squares , using the GS algorithm can effectively detect wavefront distortion while recovering blurred images contaminated by aberrations. Due to its simple structure, high measurement accuracy and no special requirements for light sources, this technology has been widely used in the fields of remote sensing and wavefront detection, and has received extensive attention and research from domestic and foreign scientific researchers....

AI Technical Summary

Problems solved by technology

[0003] However, the current phase difference method still has many limitations: the phase difference method is essentially an image-based inversion technology, which needs to extract wavefront information and restore the image according to the collected light intensity information, which is artificially introduced as prior information The aberration of the image will inevitably cause the image to lose part of the information, thereby affecting the accuracy of wavefront detection and the quality of the restored image, and the ability of the phase difference method to detect wavefront distortion is therefore restricted; in the application field with high requirements for resolution, For example, in astronomical observation, the aperture of the imaging system needs to be made very large, and the pixel size of common CCDs is difficult to satisfy the Nesquit sampling law, and interpolation is often required in the back-end algorithm processing, which affects the restoration accuracy of the phase difference algorithm; The currently widely used phase difference wavefront detection and imaging systems require additional optical components, such as beam splitters and reflectors, special ones such as the grating used in the invention patent CN102331303, and the combined prism proposed by the invention patent CN102564612B. These optical components The use of can ensure the real-time performance of image acquisition and enhance the ability to detect high-frequency aberrations, but it increases the volume, complexity and cost of the system, and introduces additional system errors and unknown aberrations, which seriously affects the accuracy of the algorithm.

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