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Incoherent Change Detection Methods for Wavelength-Resolution SAR Image Stacks Based on Masking Techniques
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- Alves, Dimas, I (author)
- Fed Univ Pampa UNIPAMPA, BRA
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- Muller, Cristian (author)
- Fed Univ Pampa UNIPAMPA, BRA
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- Vu, Viet Thuy, 1977- (author)
- Blekinge Tekniska Högskola,Institutionen för matematik och naturvetenskap
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- IEEE, 2020
- 2020
- English.
- In: 2020 IEEE National Radar Conference - Proceedings. - : IEEE. - 9781728189420
- Conference paper (peer-reviewed)
Abstract
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- This paper presents two incoherent change detection methods for wavelength-resolution synthetic aperture radars (SAR) image stacks based on masking techniques. The first technique proposed is the Simple Masking Detection (SMD). This method uses the statistical behavior of pixels-sets in the image stack to create a binary mask, which is used to remove pixels that are not related to changes in a surveillance image from the same interest region. The second technique is the Multiple Concatenated Masking Detection (MCMD), which produces a more selective mask than the SMD by concatenating multiple masks from different image stacks. The MCMD can be used in specific applications where multiple stacks share common patterns of target deployments. Both proposed techniques were evaluated using 24 incoherent SAR images obtained by the CARABAS II system. The experimental results revealed that the proposed detection methods have better performance in terms of probability of detection and false alarm rate when compared with other change detection techniques, especially for high detection probabilities scenarios.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Naturresursteknik -- Fjärranalysteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Environmental Engineering -- Remote Sensing (hsv//eng)
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