Electronics Optics & Control, Volume. 27, Issue 7, 77(2020)

Raindrop Removal in a Single Image Based on Conditional Generative Adversarial Networks

ZHU Min1... FANG Chao1 and QI Meibin2 |Show fewer author(s)
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  • 1[in Chinese]
  • 2[in Chinese]
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    Rainy weather will greatly worsen the image quality and hinder the subsequent processing of the image.In order to realize raindrop removal in the image, a single-image raindrop removal method based on Conditional Generative Adversarial Networks (CGAN) is proposed.This method adopts the basic framework of CGAN, uses the raindrop image as additional condition information and adds Lipschitz constraints.The network model is trained by combining condition adversarial loss, content loss with perception loss to repair the raindrop area and reconstruct the image.The experimental results show that the proposed method has better raindrop removal effects than the existing algorithms, and can avoid image blurring on the basis of ensuring the raindrop removal effect.

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    ZHU Min, FANG Chao, QI Meibin. Raindrop Removal in a Single Image Based on Conditional Generative Adversarial Networks[J]. Electronics Optics & Control, 2020, 27(7): 77

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    Paper Information

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    Received: Jul. 9, 2019

    Accepted: --

    Published Online: Jan. 19, 2021

    The Author Email:

    DOI:10.3969/j.issn.1671-637x.2020.07.015

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