CONFERENCE PROCEEDINGS
Advanced Search
Home > Journals > J. Appl. Rem. Sens. > Volume 8 > Issue 1 > Article
Open Access
11 June 2014 Improving image classification in a complex wetland ecosystem through image fusion techniques
Lalit Kumar, Priyakant Sinha, Subhashni Taylor
Author Affiliations +
Journal of Applied Remote Sensing, Vol. 8, Issue 1, 083616 (June 2014). https://doi.org/10.1117/1.JRS.8.083616
Abstract
The aim of this study was to evaluate the impact of image fusion techniques on vegetation classification accuracies in a complex wetland system. Fusion of panchromatic (PAN) and multispectral (MS) Quickbird satellite imagery was undertaken using four image fusion techniques: Brovey, hue-saturation-value (HSV), principal components (PC), and Gram–Schmidt (GS) spectral sharpening. These four fusion techniques were compared in terms of their mapping accuracy to a normal MS image using maximum-likelihood classification (MLC) and support vector machine (SVM) methods. Gram–Schmidt fusion technique yielded the highest overall accuracy and kappa value with both MLC (67.5% and 0.63, respectively) and SVM methods (73.3% and 0.68, respectively). This compared favorably with the accuracies achieved using the MS image. Overall, improvements of 4.1%, 3.6%, 5.8%, 5.4%, and 7.2% in overall accuracies were obtained in case of SVM over MLC for Brovey, HSV, GS, PC, and MS images, respectively. Visual and statistical analyses of the fused images showed that the Gram–Schmidt spectral sharpening technique preserved spectral quality much better than the principal component, Brovey, and HSV fused images. Other factors, such as the growth stage of species and the presence of extensive background water in many parts of the study area, had an impact on classification accuracies.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Citation Download Citation
Lalit Kumar, Priyakant Sinha, and Subhashni Taylor "Improving image classification in a complex wetland ecosystem through image fusion techniques," Journal of Applied Remote Sensing 8(1), 083616 (11 June 2014). https://doi.org/10.1117/1.JRS.8.083616
Published: 11 June 2014
JOURNAL ARTICLE
 16 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Lens.org Logo
CITATIONS
Cited by 29 scholarly publications and 1 patent.
Advertisement
Advertisement
KEYWORDS
Image fusion
Image classification
Vegetation
Ecosystems
RGB color model
Image enhancement
Spatial resolution
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top