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

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 (...

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Main Authors: Minseok Kang, Jaemin Baek
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/21/19/6645
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author Minseok Kang
Jaemin Baek
author_facet Minseok Kang
Jaemin Baek
author_sort Minseok Kang
collection DOAJ
description 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.
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spelling doaj.art-c3abec905b274b50bcab69a542e3e4ec2023-11-22T16:49:14ZengMDPI AGSensors1424-82202021-10-012119664510.3390/s21196645SAR Image Change Detection via Multiple-Window Processing with Structural SimilarityMinseok Kang0Jaemin Baek1Division of Electrical, Electronic, and Control Engineering, Kongju National University, Cheonan 31080, KoreaDepartment of Mechanical Engineering, Gangneung-Wonju National University, Wonju 26403, KoreaIn 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.https://www.mdpi.com/1424-8220/21/19/6645change detectionmultiple-window processinggamma correctionsynthetic aperture radarstructural similarity index measure
spellingShingle Minseok Kang
Jaemin Baek
SAR Image Change Detection via Multiple-Window Processing with Structural Similarity
Sensors
change detection
multiple-window processing
gamma correction
synthetic aperture radar
structural similarity index measure
title SAR Image Change Detection via Multiple-Window Processing with Structural Similarity
title_full SAR Image Change Detection via Multiple-Window Processing with Structural Similarity
title_fullStr SAR Image Change Detection via Multiple-Window Processing with Structural Similarity
title_full_unstemmed SAR Image Change Detection via Multiple-Window Processing with Structural Similarity
title_short SAR Image Change Detection via Multiple-Window Processing with Structural Similarity
title_sort sar image change detection via multiple window processing with structural similarity
topic change detection
multiple-window processing
gamma correction
synthetic aperture radar
structural similarity index measure
url https://www.mdpi.com/1424-8220/21/19/6645
work_keys_str_mv AT minseokkang sarimagechangedetectionviamultiplewindowprocessingwithstructuralsimilarity
AT jaeminbaek sarimagechangedetectionviamultiplewindowprocessingwithstructuralsimilarity