AccuracyAssessment of Supervised and Unsupervised Image Classification of Fused Satellite Images
Main Article Content
Abstract
Remote sensing techniques have been extensively utilized for recognition of land use and land cover structures. Land evidence can be definitely composed by classification of satellite images in the perspective of their practice. In this paper study area has been classified into five classes i.e. vegetation, agriculture, water body, open area and urban land by classification of fused images obtained from various fusion techniques. The spatial and spectral determinations of various satellite images make availableimprovedevidence with the encouragementof imageprocessing and image fusion of both multispectral and spatial images. The input images fused together are multispectral image and panchromatic images obtained from IRS-1D satellite utilizing LISS III. Matlab 10.0 software has been used for image processing, fusion and classification of the images. The Principal Component Analysis (PCA), wavelet transform, fuzzy and neuro fuzzy techniques arehave been used for image fusion. The resultant images have been classified using the supervised and unsupervised classification techniques;decision tree classifier and K-Meansalgorithms and evaluationconcerning them in standings of their accuracy.
Keywords:fusion,classification,accuracy,PCA,wavelet,neuro fuzzy
Keywords:fusion,classification,accuracy,PCA,wavelet,neuro fuzzy
Downloads
Download data is not yet available.
Article Details
Section
Articles
COPYRIGHT
Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
- The journal allows the author(s) to retain publishing rights without restrictions.
- The journal allows the author(s) to hold the copyright without restrictions.