NDLI: SAR image change detection based on deep denoising and CNN

Content Provider	IET Digital Library
Author	Cao, Xianghai Ji, Yamei Wang, Lin Ji, Beibei Jiao, Licheng Han, Jungong
Abstract	The intrinsic noise of synthetic aperture radar (SAR) images has a big influence to the image processing performance, especially in change detection (CD). Image denoising is an important branch of image restoration which aims at enhancing the quality of images. The detection accuracy of CD depends greatly on the quality of red difference image (DI), therefore image denoising can be regarded as a vital step in SAR CD. However, few researches focused on this problem. In this study, an end-to-end deep denoising model is first designed to remove the noise of SAR images. With the help of abundant simulated SAR images, deep denoising model is trained effectively to estimate the noise component. Then clean image can be achieved by removing this noise component from the original SAR image. After denoising, the new image pair will generate a clean DI. At last, DI is classified into changed and unchanged areas by a three-layer Convolutional Neural Network (CNN). Three real SAR image pairs demonstrate the effectiveness of the proposed method.
Starting Page	1509
Ending Page	1515
Page Count	7
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 9, Jul (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5172
Journal	IET Image Processing
Publisher Date	2019-04-29
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Abundant Simulated SAR Image Clean Image Computer Vision And Image Processing Technique Detection Accuracy End-to-end Deep Denoising Model Image Denoising Image Pair Image Processing Image Processing Performance Image Restoration Intrinsic Noise Noise Component Optical, Image And Video Signal Processing Original SAR Image Radar Equipment Radar Imaging Red Difference Image SAR CD SAR Image Change Detection SAR Image Pairs Synthetic Aperture Radar Synthetic Aperture Radar Image System And Application
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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