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GAN (generative adversarial network) based image raindrop removal method

A network, raindrop technology, applied in the field of image filtering and machine learning, can solve problems such as distortion, achieve good results, clear and intuitive images

Active Publication Date: 2018-06-29
SUN YAT SEN UNIV
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Problems solved by technology

[0007] However, the effect of the picture generated by using the above technology will have some defects, especially in the part where the background is similar to the raindrops, it will often be distorted

Method used

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  • GAN (generative adversarial network) based image raindrop removal method
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  • GAN (generative adversarial network) based image raindrop removal method

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Embodiment Construction

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0027] figure 1 It is the overall flowchart of the embodiment of the present invention, such as figure 1 As shown, the method includes:

[0028] S1, obtaining the exterior scene picture set from the database;

[0029] S2, image preprocessing, adding a rain effect to the acquired exterior picture set, and constructing a training set and a test set;

[0030] S3, constructing a generative network, whose input is a rainy scene image, and the output is a clear scene ...

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Abstract

An embodiment of the invention discloses a GAN (generative adversarial network) based image raindrop removal method. The method is mainly characterized in that one more efficient and more remarkable image rain removal method is provided with a deep rain removal algorithm by constructing the GAN, in actual use, all that is needed is to input an image into the generative network, a result image canbe obtained by one-time forward propagation, and the method has more efficient effect as compared with the traditional image processing method; besides, details of part of rain removal effects can beadjusted by introducing sense correlation of feature space into a model, so that the generated image is clearer and more visual, and better effect can be realized in image enhancement.

Description

technical field [0001] The invention relates to the technical field of image filtering and the field of machine learning, in particular to a method for removing raindrops from an image based on a generative confrontation network. Background technique [0002] With the rapid development of smart phones in recent years, more and more people use mobile phones for location shooting. When shooting on location, it is often due to rainy weather, and the pictures taken often have some raindrops or rain streaks in the scene. Therefore, in order to obtain a clearer image, it is necessary to perform certain processing on the image. With the development of computers and the continuous research of deep learning in recent years, it is more effective and feasible to use more effective deep learning methods to solve traditional research problems. [0003] Convolutional neural network (CNN) is a variant of multi-layer perceptron (MLP). CNN's performance on traditional samples is not as goo...

Claims

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T2207/20081G06T5/73
Inventor 曾坤郭浩翀林谋广
Owner SUN YAT SEN UNIV
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