SAR image time-series analysis framework using morphological operators and   global and local information-based linear discriminant analysis

Ufuk SAKARYA; Caner DEMİRPOLAT

Makale detayları

SAR image time-series analysis framework using morphological operators and global and local information-based linear discriminant analysis

Yazarlar:

Ufuk SAKARYA | Caner DEMİRPOLAT

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 6, pp.2958-2966

Belge Tipi:

Makale

Yayın Tarihi:

11/2018

Belge Dili:

Türkçe

Document ID (Org No.):

2000734504

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

Fusion of spectral, spatial, and temporal information is   an effective method used in many satellite remote sensing applications. On   the other hand, one drawback of this fusion is an increase in complexity. In   this paper, we focus on developing a fast and well-performed classification   method for agricultural crops using time-series SAR data. In order to   achieve this, a novel two-stage approach is proposed. In the first stage, a   high-dimensional feature space is obtained using time-series dual-pol SAR   data and morphological operators. Spectral, spatial, and temporal   information is combined into a single high-dimensional feature space. In the   second stage, a dimension reduction technique is applied to the feature   vector in order to decrease time complexity and increase classification   accuracy by considering the global and local pattern information in the   high-dimensional feature space. The contribution of the morphological   profiles to the classification performance is significant; however the time   complexity is increased drastically. The proposed method overcomes the time   complexity stemming from high-dimensional feature space; it also improves   the classification performance. The superiority of the proposed method to   the comparative methods in agricultural crop classification is   experimentally shown with the improvements in both classification and time   performance using time-series TerraSAR-X images.

Makale detayları

SAR image time-series analysis framework using morphological operators and global and local information-based linear discriminant analysis

Yazarlar: Ufuk SAKARYA | Caner DEMİRPOLAT

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 6, pp.2958-2966

Belge Tipi: Makale

Yayın Tarihi: 11/2018

Belge Dili: Türkçe

Document ID (Org No.): 2000734504

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

Ufuk SAKARYA | Caner DEMİRPOLAT

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 6, pp.2958-2966

Belge Tipi:

Makale

Yayın Tarihi:

11/2018

Belge Dili:

Türkçe

Document ID (Org No.):

2000734504

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632