Spatial variation point diffusion function smoothing method based on simple lens calculating imaging

Abstract

The invention provides a spatial variation point diffusion function smoothing method based on simple lens calculating imaging. The method is characterized by fully using characteristics of sparsity, similarity and the like of a single lens fuzzy kernel; firstly, using a blind convolution algorithm to estimate a fuzzy kernel of each image block, and combining fuzzy kernel TV priori; and then carrying out smoothing and de-noising processing on the fuzzy kernel, and based on a filtered PSF of neighborhood information, replacing an existing PSF. Compared to the prior art, by using the method of the invention, a complex experiment environment and equipment are not needed, the spatial variational PSF can be estimated through combining a correlation algorithm based on a simple lens system; robustness of a deconvolution process is increased; and a noise, a ringing effect and the like are restrained.

Description

technical field [0001] The invention mainly relates to the field of digital image processing, in particular to a space-varying PSF (point spread function) smoothing method based on simple lens calculation imaging. Background technique [0002] In modern optical systems, image quality will be reduced due to optical errors, and most single-convex lenses with spherical mirror structures will be affected by such as chromatic aberration, spherical aberration, and coma. In order to solve this dilemma, the existing optical imaging system mainly compensates for the aberration of the single lens through complex combination lenses. For example, the lens of a SLR camera may contain dozens of independent single lenses or lens groups. However, while the design of the complex combination lens improves the imaging quality, it undoubtedly greatly increases the cost of lens design and manufacture, and the volume and weight of the lens also increase thereupon. Therefore, how to reduce the de...

AI Technical Summary

Problems solved by technology

[0007] In view of the inaccurate estimation of the spatially varying blur kernel in the existing simple lens imaging method, the calculation process takes too long, and the complex experimental environment is difficult to realize, etc., the purpose of the present invention is to provide a spatially varying point spread function based on simple lens calculation imaging Smoothing method, this method makes full use of the sparsity and similarity of the single-lens blur kernel. First, the blind convolution algorithm is used to estimate the blur kernel of each image block, combined with the blur kernel TV prior, and then the blur kernel is smoothed and Denoising processing, replacing the existing PSF with the filtered PSF based on neighborhood information

Images