title   
  

On the effect of synthetic morphological feature vectors on hyperspectral image classification performance (Yapay biçimbilimsel özniteliklerin hiperspektral görüntü sınıflandırma başarımının üzerindeki etkisi)

Davari, Amir Abbas and Aptoula, Erhan and Yanıkoğlu, Berrin (2015) On the effect of synthetic morphological feature vectors on hyperspectral image classification performance (Yapay biçimbilimsel özniteliklerin hiperspektral görüntü sınıflandırma başarımının üzerindeki etkisi). In: 23th Signal Processing and Communications Applications Conference (SIU 2015), Malatya, Turkey

[img]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
358Kb

Official URL: http://dx.doi.org/10.1109/SIU.2015.7129909

Abstract

This paper studies the effect of synthetic feature vectors on the classification performance of hyperspectral remote sensing images. As feature vectors, it has been chosen to employ morphological attribute profiles, that have proven themselves in this field. At this early stage of our work, the relatively simple Bootstrapping algorithm has been used for synthetic feature vector generation. Based on experiments conducted on multiple hyperspectral datasets, it has been observed that synthetic feature vectors contribute considerably to classification performance in the case of limited training dataset sizes.

Item Type:Papers in Conference Proceedings
Subjects:UNSPECIFIED
ID Code:27616
Deposited By:Berrin Yanıkoğlu
Deposited On:08 Dec 2015 16:16
Last Modified:08 Dec 2015 16:16

Repository Staff Only: item control page