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基于结构相似性的多窗口处理的 SAR 图像变化检测。

SAR Image Change Detection via Multiple-Window Processing with Structural Similarity.

机构信息

Division of Electrical, Electronic, and Control Engineering, Kongju National University, Cheonan 31080, Korea.

Department of Mechanical Engineering, Gangneung-Wonju National University, Wonju 26403, Korea.

出版信息

Sensors (Basel). 2021 Oct 6;21(19):6645. doi: 10.3390/s21196645.

DOI:10.3390/s21196645
PMID:34640964
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8512958/
Abstract

In this paper, a synthetic aperture radar (SAR) change detection approach is proposed based on a structural similarity index measure (SSIM) and multiple-window processing (MWP). The proposed scheme is performed in two steps: (1) generation of a coherence image based on MWP associated with SSIM and (2) gamma correction (GC) filtering. The proposed method is capable of providing a high-quality coherence image because the MWP operation based on SSIM has high sensitivity to the similarity measure for intensity between two SAR images. By finding an optimum value of order of GC, the proposed method can considerably reduce the effect of speckle noise on the coherence image, while retaining nearly all the information related to changed region involved in the change detection map. Several experimental results are presented to demonstrate the effectiveness of the proposed scheme.

摘要

本文提出了一种基于结构相似性指数度量 (SSIM) 和多窗口处理 (MWP) 的合成孔径雷达 (SAR) 变化检测方法。该方案分两步进行：(1) 基于与 SSIM 相关的 MWP 生成相干图像，(2) 伽马校正 (GC) 滤波。该方法能够提供高质量的相干图像，因为基于 SSIM 的 MWP 操作对两幅 SAR 图像之间的强度相似性度量具有很高的灵敏度。通过找到 GC 阶数的最佳值，该方法可以大大减少斑点噪声对相干图像的影响，同时保留与变化检测图中涉及的变化区域相关的几乎所有信息。本文给出了几个实验结果，以证明所提出方案的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/c6aa1de2422e/sensors-21-06645-g012a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/8060feba9981/sensors-21-06645-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/0a9f8d729676/sensors-21-06645-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/f43aa6a758b7/sensors-21-06645-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/34eba54c77df/sensors-21-06645-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/2afdb3173844/sensors-21-06645-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/2697ab4bf3cd/sensors-21-06645-g008a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/38cd14187181/sensors-21-06645-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/732c35834796/sensors-21-06645-g010a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/0d99c2d00087/sensors-21-06645-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/c6aa1de2422e/sensors-21-06645-g012a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/8060feba9981/sensors-21-06645-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/78c1aa7b3557/sensors-21-06645-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/14336d2aa9df/sensors-21-06645-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/0a9f8d729676/sensors-21-06645-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/f43aa6a758b7/sensors-21-06645-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/34eba54c77df/sensors-21-06645-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/2afdb3173844/sensors-21-06645-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/2697ab4bf3cd/sensors-21-06645-g008a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/38cd14187181/sensors-21-06645-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/732c35834796/sensors-21-06645-g010a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/0d99c2d00087/sensors-21-06645-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a372/8512958/c6aa1de2422e/sensors-21-06645-g012a.jpg

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本文引用的文献

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Deep SAR Imaging and Motion Compensation.深度合成孔径雷达成像与运动补偿
IEEE Trans Image Process. 2021;30:2232-2247. doi: 10.1109/TIP.2021.3051484. Epub 2021 Jan 26.
2
ISAR Imaging of High-Speed Maneuvering Target Using Gapped Stepped-Frequency Waveform and Compressive Sensing.基于频移步进和压缩感知的高速机动目标 ISAR 成像
IEEE Trans Image Process. 2017 Oct;26(10):5043-5056. doi: 10.1109/TIP.2017.2728182. Epub 2017 Jul 17.
3
On the mathematical properties of the structural similarity index.结构相似性指数的数学性质。
IEEE Trans Image Process. 2012 Apr;21(4):1488-99. doi: 10.1109/TIP.2011.2173206. Epub 2011 Oct 24.
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Multiresolution registration of remote sensing imagery by optimization of mutual information using a stochastic gradient.利用随机梯度优化互信息进行遥感图像的多分辨率配准
IEEE Trans Image Process. 2003;12(12):1495-511. doi: 10.1109/TIP.2003.819237.
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Image quality assessment: from error visibility to structural similarity.图像质量评估：从误差可见性到结构相似性。
IEEE Trans Image Process. 2004 Apr;13(4):600-12. doi: 10.1109/tip.2003.819861.