Performance evaluation of different classifiers (Isoseg, Bhattacharyya, Maxver e Maxver-ICM), using CCD/CBERS-1 and ETM+/Landsat-7 fused images
Wilson Lins de Mello Filho, Camila Aguirre Góes, Melissa Carvalho
Revista Ambiente & Água · 2007
doi:10.4136/ambi-agua.27 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
The aim of this study was to compare the performance of image classifiers (Isoseg, Bhattacharyya, Maxver and Maxver-ICM) based on an accuracy analysis (set percentage, area determination and Kappa coefficient), using as ground truth an edited thematic map. For this, pre-processing techniques (atmospheric, geometric and radiometric corrections), contrast enhancement (IHS data fusion and principal component analysis) and classification of CCD/CBERS-1 and ETM+/Landsat-7 images were done. Amongst all classifiers tested, Isoseg and Bhattacharyya presented best performance for the studied classes and the study area. It is anticipated that these results are relevant to environmental analyses based on orbital satellite data.
Abstract licence: CC BY
References11
11 more references, whose wording the paper’s licence keeps private.
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.