Unsupervised SAR Image Change Detection Based on Structural Consistency and CFAR Threshold Estimation Article Swipe
Jingxing Zhu
,
Feng Wang
,
Hongjian You
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/rs15051422
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/rs15051422
Despite the remarkable progress made in recent years, until today, the automatic detection of changes in synthetic aperture radar (SAR) images remains a difficult task due to speckle noise. This inherent multiplicative noise tends to increase false alarms and misdetections. As a solution, we developed an unsupervised method that detects SAR changes by analyzing structural differences. By this method, the spatial structure cues of a pixel are represented by a set of similarity weight vectors calculated from the non-local scale of the pixel. The difference image (DI) is then derived by measuring the structural consistency of the corresponding pixels. A new statistical distance that is insensitive to speckle noise was used to measure the similarity weights between patches in order to obtain an accurate structure. It was derived by applying the Nakagami–Rayleigh distribution to a statistical test and customizing the approximation based on change detection. The CFAR threshold estimator in conjunction with the Rayleigh hypothesis was then employed to attenuate the effect of the unimodal histogram of the DI. The results indicated that the proposed method reduces the false alarm rate and improves the kappa and F1-scores, while providing satisfactory visual results.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/rs15051422
- https://www.mdpi.com/2072-4292/15/5/1422/pdf?version=1677831760
- OA Status
- gold
- Cited By
- 10
- References
- 52
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4323045931
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4323045931Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/rs15051422Digital Object Identifier
- Title
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Unsupervised SAR Image Change Detection Based on Structural Consistency and CFAR Threshold EstimationWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-03-03Full publication date if available
- Authors
-
Jingxing Zhu, Feng Wang, Hongjian YouList of authors in order
- Landing page
-
https://doi.org/10.3390/rs15051422Publisher landing page
- PDF URL
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https://www.mdpi.com/2072-4292/15/5/1422/pdf?version=1677831760Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2072-4292/15/5/1422/pdf?version=1677831760Direct OA link when available
- Concepts
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Artificial intelligence, Computer science, Pattern recognition (psychology), Synthetic aperture radar, Constant false alarm rate, Speckle pattern, Pixel, Speckle noise, Histogram, Noise (video), Change detection, Computer vision, Mathematics, Image (mathematics)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
10Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 5, 2024: 5Per-year citation counts (last 5 years)
- References (count)
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52Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| publication_date | 2023-03-03 |
| publication_year | 2023 |
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