Image deblurring method and system based on deep neural network parameter estimation

Abstract

The invention discloses an image deblurring method and system based on deep neural network parameter estimation, and the method comprises the steps: obtaining a training set and a test set, and carrying out the preprocessing; setting network parameters; performing gaussian blur removal on the image based on deep neural network parameter estimation, wherein the deep neural network comprises two sub-modules, namely a Gaussian standard deviation level parameter estimation sub-module and a non-blind deblurring sub-module, the Gaussian standard deviation horizontal parameter estimation sub-module is of an hourglass type network structure, a skip connection mechanism is used between a decoding block and a coding block in a symmetric layer; carrying out PCA principal component analysis on a Gaussian blurred kernel, then carrying out dimension stretching to obtain a vector graph, and taking the vector graph and a blurred image as input of the non-blind deblurring module; enabling the non-blinddeblurring sub-module to execute a non-linear mapping process by applying cascaded convolution layers; and training a neural network, and testing the neural network to obtain a deblurring result. Themethod is applied to image deblurring, and a good effect can be achieved.

Description

technical field [0001] The invention belongs to the field of video or image deblurring, and in particular relates to an image deblurring method and system based on deep neural network parameter estimation. Background technique [0002] Image deblurring is an important research direction in image processing. With the development of neural network technology and traditional methods in recent years, technologies such as license plate recognition, face recognition, and pedestrian re-identification have become mature. However, during the process of image acquisition, processing, storage, transmission, etc., the image quality will always be degraded due to unpredictable factors such as shooting devices or weather. Blurring is an important manifestation of image quality degradation. Image deblurring is an important preprocessing step for many computer vision tasks, and it is widely used in license plate recognition, face recognition and other fields. [0003] The specific manife...

AI Technical Summary

Problems solved by technology

However, this method cannot effectively deal with the situation where the blur intensity is large, and the scope of application is relatively small.

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