Missile-borne image deblurring method based on generative adversarial network

Abstract

The invention discloses a missile-borne image deblurring method based on a generative adversarial network, and belongs to the technical field of missile-borne computer vision. According to the method, a fuzzy missile-borne image is deblurred by using a generative adversarial network, a deep convolutional generative adversarial network model comprising a generator and a discriminator is designed, the generator adopts a coding-decoding structure, a joint loss function is constructed, and continuous training is performed to generate a restored image of the missile-borne blurred image. A distinct image and an image forged by a generator are distinguished through a discriminator, the generator approaches the distinct image confusion discriminator, a network model reaches an expected index through adversarial training of two networks, and the network model after adversarial training is transplanted to a missile-borne computer for deblurring a missile-borne image and improving guidance precision. Besides, different fuzzy sources are simulated by establishing a vivid semi-physical simulation system for synthesizing motion blur, the problem that actual acquisition of missile-borne image data is difficult is solved, the training efficiency is improved, and the test cost is saved.

Description

technical field [0001] The invention belongs to the technical field of missile-borne computer vision, and in particular relates to a method for deblurring a missile-borne image. Background technique [0002] When the low-speed rolling projectile hits the target, due to the strapdown between the TV camera and the projectile body, the rapid movement, continuous rotation, and vibration of the projectile cause the quality of the acquired image to decline, resulting in distortion, blurring, and blurring of the collected field of view image. Problems such as defocusing will bring great difficulties to subsequent target detection and tracking, so the deblurring research of missile images is of great significance. [0003] Image deblurring refers to obtaining a clear image from a degraded image. It is an ill-posed problem and can be divided into two cases: blind image deblurring and non-blind image deblurring. Image non-blind deblurring refers to recovering a clear image when the b...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem of serious blurring in the missile-borne image: the acquired image contains a lot of noise, jitter and blur characteristics, resulting in a serious decline in image quality, making it difficult to accurately identify the target in the missile-borne image, resulting in a decrease in the accuracy of image guidance

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