Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3260
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dc.contributor.authorKanth, P. Chandra-
dc.contributor.authorGupta, Neha-
dc.contributor.authorAri, Samit-
dc.date.accessioned2019-03-12T04:27:55Z-
dc.date.available2019-03-12T04:27:55Z-
dc.date.issued2019-02-
dc.identifier.citation3rd IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT 2019), Coimbatore, India 20 – 22 February 2019en_US
dc.identifier.urihttp://hdl.handle.net/2080/3260-
dc.descriptionCopyright of this document belongs to proceedings publisher.en_US
dc.description.abstractIn this paper, an unsupervised global threshold technique, which is based on histogram analysis, is proposed. This technique analyzes the histogram. The histogram is partitioned in intensities at equal interval, and each interval assigned as single intensity. Then, differentiation is applied to get location of maxima in histogram. Depending on the locations of maxima, threshold is calculated to separate the two regions as change and no-change. The utilization of the differentiation improves the visualization of the maxima of different regions. To demonstrate the effectiveness of technique, experiments are conducted on two multispectral satellite images.en_US
dc.subjectBinary change mapen_US
dc.subjectChange detectionen_US
dc.subjectHistogram analysisen_US
dc.subjectMultispectral satellite imageen_US
dc.subjectThresholdingen_US
dc.titleChange Detection in Multispectral Satellite Images using Histogram based Thresholding Techniqueen_US
dc.typeArticleen_US
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