Image defogging method based on lightweight convolutional neural network

Abstract

The invention discloses an image defogging method based on a lightweight convolutional neural network in the technical field of image processing. The technical problems that in the prior art, information of an image processed through an image enhancement defogging method is lost, if parameters of the image processed through an image restoration defogging method are improperly selected, the effectof the restored image can be influenced, and the image defogging speed is influenced through a defogging algorithm based on deep learning are solved. The method comprises the following steps: inputting a foggy image into a pre-trained lightweight convolutional neural network to obtain a fogless image, wherein the lightweight convolutional neural network comprises at least two depth separable convolutional layers with different scales, and the depth separable convolutional layers comprise depth convolution and point-by-point convolution which are connected in series with each other.

Description

technical field [0001] The invention relates to an image defogging method based on a lightweight convolutional neural network, which belongs to the technical field of image processing. Background technique [0002] Due to many reasons such as garbage incineration, construction dust, and vehicle exhaust, many cities in China have been cast in the shadow of smog. The image taken in foggy weather, due to the significant decrease in contrast and color saturation, the picture is not clear enough, which affects the use effect of the picture. For example, the traffic surveillance video is blurred, resulting in deviations in the image recognition and processing process, which is not conducive to accurate recording of traffic information. Therefore, there are very urgent theoretical and practical needs to improve the image quality in foggy weather and reduce the impact of foggy weather on outdoor imaging. [0003] With the development of computer technology, video and image defoggi...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the deficiencies of the prior art, the object of the present invention is to provide an image defogging method based on a lightweight convolutional neural network to solve the problem of information loss in the image processed by the image enhancement defogging method in the prior art, and the use of image If the image processed by the restored defogging method is improperly selected, it will affect the effect of the restored image, and the technical problem of using the defogging algorithm based on deep learning will affect the speed of image defogging

Images