This paper proposes a new unsupervised satellite change de- tection method, which is invariant to shadow and shading e ects. To achieve this, rstly, the RGB satellite images are transformed into spher- ical colour space to remove illumination artifacts. Then, a new unsuper- vised change detection is used. The resultant optimal binary change mask is obtained by minimisation a mean square error based cost function us- ing Binary Particle Swarm Optimisation (BPSO). The proposed method is compared with three other satellite change detection methods and the results demonstrate that our method provides a signi cant improvement of obtaining the changed and unchanged regions on the diference image. The total errors show that our method at least 39.62% better than the best compared method and are utmost 176.18% better than the worst one.
Eser Adı (dc.title) | Unsupervised Satellite Change Detection Using Particle Swarm Optimisation in Spherical Coordinates |
Yayın Türü (dc.type) | Konferans Bildirisi |
Yazar/lar (dc.contributor.author) | UŞAKLI, Ali Bülent |
Yazar/lar (dc.contributor.author) | YAVARIABDI, Amir |
Yazar/lar (dc.contributor.author) | KUSETOĞULLARI, Hüseyin |
Atıf Dizini (dc.source.database) | Wos |
Atıf Dizini (dc.source.database) | Scopus |
Konu Başlıkları (dc.subject) | Remote Sensing |
Konu Başlıkları (dc.subject) | Change Detection |
Konu Başlıkları (dc.subject) | Spherical Coordinate System |
Konu Başlıkları (dc.subject) | Optimisation |
Konu Başlıkları (dc.subject) | Binary Particle Swarm Optimisation |
Yayın Tarihi (dc.date.issued) | 2015 |
Kayıt Giriş Tarihi (dc.date.accessioned) | 2019-07-09T14:07:52Z |
Açık Erişim tarihi (dc.date.available) | 2019-07-09T14:07:52Z |
Özet (dc.description.abstract) | This paper proposes a new unsupervised satellite change de- tection method, which is invariant to shadow and shading e ects. To achieve this, rstly, the RGB satellite images are transformed into spher- ical colour space to remove illumination artifacts. Then, a new unsuper- vised change detection is used. The resultant optimal binary change mask is obtained by minimisation a mean square error based cost function us- ing Binary Particle Swarm Optimisation (BPSO). The proposed method is compared with three other satellite change detection methods and the results demonstrate that our method provides a signi cant improvement of obtaining the changed and unchanged regions on the diference image. The total errors show that our method at least 39.62% better than the best compared method and are utmost 176.18% better than the worst one. |
Yayın Dili (dc.language.iso) | en |
Tek Biçim Adres (dc.identifier.uri) | https://hdl.handle.net/20.500.12498/936 |