政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/147030

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/147030

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政大典藏 > College of Informatics > Department of Computer Science > Theses > Item 140.119/147030

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/147030

Title:	自監督式學習的單張影像除雨技術 Self-supervised Single Image Deraining
Authors:	李偉華 Li, Wei-Hua
Contributors:	彭彥璁 Peng, Yan-Tsung 李偉華 Li, Wei-Hua
Keywords:	影像處理影像除雨自監督式學習 Image processing Image deraining Self-supervised learning
Date:	2023
Issue Date:	2023-09-01 15:23:59 (UTC+8)
Abstract:	單一影像除雨 (Single Image Deraining) 的任務目標在於去除單一影像中的雨紋，該領域近年來引起了許多關注。近期在這個主題的研究，主要集中在深度學習中的監督式學習方法上，該方法使用下雨場景影像與其相對應的乾淨影像來訓練模型。然而，收集成對影像的工作相當花費時間與人力成本。因此，我們提出了 Rain2Avoid (R2A)，一個只需要一張下雨場景影像就可以除雨的自監督式學習模型。我們也提出一個參考局部影像梯度來預測潛在雨紋的模組，在自監督的訓練過程中我們會略過雨紋像素，參考區域相似的像素來產生較乾淨的背景影像，並直接對輸入下雨影像進行自監督式訓練。可以預期的是自監督式的 R2A 表現可能不如有使用乾淨影像作為參考的監督式學習模型。但是當訓練的成對影像是無法取得時，R2A 就會有優勢，R2A 可以只使用一張下雨場景影像進行自監督學習。實驗結果顯示，我們所提出的方法表現得比最先進的小樣本除雨和自監督降噪方法還要良好。 It is common to take pictures outside; however, the weather may not be good. If we shoot the picture on a rainy day, we might capture rain streaks in the image. Image deraining is one of the image processing tasks, trying to remove the rain streaks on the image. Most works in these years apply a supervised image-deraining method, which relies on rainy-clean image pairs to train. However, collecting such pairwise images is strenuous and time- consuming. Therefore, some works generated synthetic rainy images, making it easier to get lots of pairwise images. However, using synthetic images to train a deraining model may not work well on real rainy images. We present a novel self-supervised method based on locally dominant gra- dient prior (LDGP) and non-local self-similarity stochastic sampling (NSSS) which can respectively extract the potential rain streak and generate the stochas- tic derain reference. With the help of LDGP and NSSS, we can self-supervise only one single image for image deraining. Extensive experiments on syn- thetic and real image datasets validate the potential of our self-supervised image-deraining method.
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Description:	碩士國立政治大學資訊科學系 110753106
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0110753106
Data Type:	thesis
Appears in Collections:	[Department of Computer Science ] Theses

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