Object recognitions in radarsat-1 sar data using fuzzy classification
This study is aimed to utilize fuzzy classification for different object detections that is urban, infrastructure and coastal water in RADARSAT-1 SAR S2 mode data. Prior to fuzzy classification, Lee algorithm with kernel window sizes of 7 × 7 pixels and lines is implemented to S2 mode data. Indeed,...
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| Main Authors: | , , |
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| Format: | Article |
| Published: |
Academic Journals Inc.
2011
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/29665/ https://academicjournals.org/journal/IJPS/article-abstract/C527C0E24820 |
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| Summary: | This study is aimed to utilize fuzzy classification for different object detections that is urban, infrastructure and coastal water in RADARSAT-1 SAR S2 mode data. Prior to fuzzy classification, Lee algorithm with kernel window sizes of 7 × 7 pixels and lines is implemented to S2 mode data. Indeed, speckle reduction is performed using Lee algorithm. The results show that Lee algorithm is able to provide excellent information about linear infrastructure and urban features in SAR data. Further, fuzzy classification can discriminate between urban zone and coastal waters. In conclusion, the integration between Lee algorithm and fuzzy classification can be used for different object recognitions in S2 mode data. |
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