Optical aberration blur removing method based on deep learning

Abstract

The invention discloses an optical aberration blur removing method based on deep learning. The method comprises the following steps: 1) obtaining a point spread function of the optical system with aberration; 2.1) selecting a high-resolution image, and performing energy domain transformation to obtain an energy domain image; 2.2) performing block convolution on the energy domain image by using thecalculated correction point diffusion matrix to obtain an energy domain simulation fuzzy graph; 2.3) performing numerical domain transformation on the energy domain simulation blurred image to obtainan aberration blurred image, and forming an aberration blurred data set; 3) based on the aberration fuzzy data set, training an aberration correction neural network; and 4) correcting an image shot by the aberration optical system developed and produced by using the optical parameters through the aberration correction neural network obtained by training in the step 3) to obtain a corrected image.When the method is used, optical parameters of a camera (camera head) are operated by adopting the method disclosed by the invention, and image blurring caused by aberration of an optical system canbe well eliminated.

Description

technical field [0001] The invention belongs to an optical correction method in the field of digital image processing, and relates to an optical aberration blur removal method based on deep learning. Background technique [0002] In recent years, researchers have well-studied the blurring caused by factors such as camera shake, object motion, and defocusing, but the aberration of optical system, which also introduces image blurring, has been ignored. In traditional optical design, optical aberration is generally optimized by increasing the complexity of the optical system. However, this solution is more likely to be limited by factors such as processing costs and lens volume in light and small optical systems such as mobile phone lenses. Therefore, it is necessary to correct the residual aberration of the optical system and improve the imaging quality of the system through a software solution. [0003] Existing work on image restoration for lens aberration blur can be divid...

AI Technical Summary

Problems solved by technology

However, the previous learning-based algorithms usually have the problem of being unable to obtain strict registration of blurred image and clear image image pairs, and real-time shooting experiments are time-consuming and labor-intensive, and the workload is large when dealing with various optical systems.

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