The full text of this article


Low-illuminated SPOT-5 image improvement for density-based vegetation identification using three-layer colour manipulation approach
by Nursyafikah Hamid; Hishammuddin Asmuni; Rohayanti Hassan; Razib M. Othman
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 11, No. 1/2, 2018


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.

Online publication date: Wed, 30-May-2018


is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Advanced Intelligence Paradigms (IJAIP):
Login with your Inderscience username and password:


    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email