A spectral-spatial classification algorithm for multispectral remote sensing data

Karakahya H., Yazgan B., Ersoy O.

ARTIFICAIL NEURAL NETWORKS AND NEURAL INFORMATION PROCESSING - ICAN/ICONIP 2003, cilt.2714, ss.1011-1017, 2003 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 2714
  • Basım Tarihi: 2003
  • Dergi Adı: ARTIFICAIL NEURAL NETWORKS AND NEURAL INFORMATION PROCESSING - ICAN/ICONIP 2003
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, EMBASE, MathSciNet, Philosopher's Index, zbMATH
  • Sayfa Sayıları: ss.1011-1017
  • İstanbul Teknik Üniversitesi Adresli: Hayır

Özet

This paper aims at achieving improved land cover classification performance over conventional per-pixel classifiers as well as spectral-spatial classifiers such as ECHO (Extraction and Classification of Homogeneous Objects) algorithm. The proposed algorithm is a two-stage process, which makes use of the contextual information from neighboring pixels. First, a spatial filter is used to achieve more homogeneous regions. Secondly, maximum likelihood pixel classifier is employed to classify the land covers. The experimental results indicate that improved classification accuracy and smoother (more acceptable) thematic maps are achieved than what is obtained with the other methods considered.