A Derain System Based on GAN and Wavelet

Xiaozhang Huang ()
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Xiaozhang Huang: School of Economics and Management, Beijing Institute of Graphic Communication

A chapter in LISS 2021, 2022, pp 714-721 from Springer

Abstract: Abstract This paper proposes an image rain removal method based on wavelet thresholding and generative adversarial networks for removing rain traces on the target image to restore the original image. This paper first uses wavelet threshold denoising to pre-process the image to remove the non-rain noise and part of the image's rain noise. After that, this paper uses the generator in the adversarial generative network to complete the rain-containing images' de-rain operation. The generators and discriminators in the adversarial generative network need to be trained in advance, and the artificially generated dataset is used for training in this paper. Finally, this paper conducts experiments on the actual rain trace image dataset and artificially generated rain trace image dataset, respectively, to verify the method's effectiveness in this paper.

Keywords: Image derain; GAN; Wavelet threshold denoising (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-981-16-8656-6_63

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DOI: 10.1007/978-981-16-8656-6_63

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