Title: Low-illuminated SPOT-5 image improvement for density-based vegetation identification using three-layer colour manipulation approach

Authors: Nursyafikah Hamid; Hishammuddin Asmuni; Rohayanti Hassan; Razib M. Othman

Addresses: Department of Software Engineering, Faculty of Computing, Universiti Teknologi Malaysia (UTM), 81310 UTM Skudai Johor, Malaysia ' Department of Software Engineering, Faculty of Computing, Universiti Teknologi Malaysia (UTM), 81310 UTM Skudai Johor, Malaysia ' Department of Software Engineering, Faculty of Computing, Universiti Teknologi Malaysia (UTM), 81310 UTM Skudai Johor, Malaysia ' Department of Software Engineering, Faculty of Computing, Universiti Teknologi Malaysia (UTM), 81310 UTM Skudai Johor, Malaysia

Abstract: Poor illumination quality of a satellite image is one of the challenges encountered in vegetation analysis, especially with regard to pan-sharpened medium spatial resolution SPOT-5 imagery. Hence, the accuracy of vegetation identification will be affected. In this paper, a three-layer colour manipulation approach is proposed to overcome this issue of low illuminated SPOT-5 images in order to increase the performance of precise vegetation identification. The SPOT-5 image is pre-processed and three layers of image enhancement techniques are used to, specifically: identify vegetation, reduce shadow appearance, as well as contrast enhancement for colour uniformities in order to improve low illumination quality of images. These steps are then followed by a supervised classification process for density-based vegetation area discrimination. This research was tested using multispectral medium spatial resolution SPOT-5 imagery covering the Ramsar convention site of Tanjung Piai located at the southernmost tip of mainland Asia over the years 2008, 2011 and 2013. The results showed that the proposed approach performed better than existing techniques when dealing with low-illuminated medium resolution multispectral imagery specifically with regard to density-based vegetation identification. The results are supported with accuracy assessments and ground truth validation.

Keywords: low illumination; illumination enhancement; medium spatial resolution; vegetation identification; multispectral image.

DOI: 10.1504/IJAIP.2018.092948

International Journal of Advanced Intelligence Paradigms, 2018 Vol.11 No.1/2, pp.110 - 131

Received: 16 Mar 2016
Accepted: 30 May 2016
Published online: 04 Jul 2018 *

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