eprintid: 5418
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/54/18
datestamp: 2023-11-09 16:17:09
lastmod: 2023-11-09 16:17:09
status_changed: 2023-11-09 16:01:36
type: article
metadata_visibility: show
creators_name: Ahmad, A.
creators_name: Abdul Ghani, M.K.
creators_name: Razali, S.
creators_name: Sakidin, H.
creators_name: Md Hashim, N.
title: Haze reduction from remotely sensed data
ispublished: pub
note: cited By 13
abstract: Haze consists of atmospheric aerosols and molecules that scatter and absorb solar radiation, thus affecting the downward and upward solar radiance to be recorded by remote sensing sensors. Haze modifies the spectral signature of land classes and reduces classification accuracy, so causing problems to users of remote sensing data. Hence, there is a need to reduce the haze effects to improve the usefulness of the data. A way to do this is by integrating spectral and statistical approaches. The result shows that the haze reduction method is able to increase the accuracy of the data statistically and visually. © 2014 Asmala Ahmad et al.
date: 2014
publisher: Hikari Ltd.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84898926933&doi=10.12988%2fams.2014.4289&partnerID=40&md5=567d6287a6d18217ba8bba8b23decf1b
id_number: 10.12988/ams.2014.4289
full_text_status: none
publication: Applied Mathematical Sciences
number: 33-36
pagerange: 1755-1762
refereed: TRUE
issn: 1312885X
citation:   Ahmad, A. and Abdul Ghani, M.K. and Razali, S. and Sakidin, H. and Md Hashim, N.  (2014) Haze reduction from remotely sensed data.  Applied Mathematical Sciences (33-36).  pp. 1755-1762.  ISSN 1312885X