Soft Computing Technique and PCA Based Unsupervised Change Detection Method in Multitemporal SAR Images

Authors

  • Shahla Pathan  Department of Electronics (Communication), RTMN University, Nagpur, Maharashtra, India
  • Pooja Thakre  Department of Electronics (Communication), RTMN University, Nagpur, Maharashtra, India

Keywords:

Remote sensing, Change detection, Multi-temporal images, K-means

Abstract

In order to get the change detection image. An unsupervised change detection algorithm context-sensitive technique multitemporal remote sensing images. Change detection analyze means that according to observations made in different times, the process of defining the change detection occurring in nature or in the state of any objects or the ability of defining the quantity of temporal effects by using multitemporal data sets. There are lots of change detection techniques met in literature. It is possible to group these techniques under two main topics as supervised and unsupervised change detection. While that process is being made, image differencing method is going to be applied to the images by following the procedure of image enhancement. After that, the method of Principal Component Analysis is going to be applied to the difference image obtained. To determine the areas that have and don’t have changes, the image is grouped as two parts by Fuzzy C-Means Clustering method. For achieving these processes, firstly the process of image to image registration is completed. As a result of this, the images are being referred to each other. After that, gray scale difference image obtained is partitioned into 3x3 non overlapping blocks. With the method of principal component analysis, eigenvector space is gained and from here, principal components are reached. Finally, feature vector space consisting principal component is partitioned into two clusters using Fuzzy C-Means Clustering and after that change detection process has been done

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International Journal of Scientific Research in Science and Technology

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Published

2017-02-28

Issue

Volume 3, Issue 2, January-February-2017

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Shahla Pathan, Pooja Thakre, " Soft Computing Technique and PCA Based Unsupervised Change Detection Method in Multitemporal SAR Images, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 3, Issue 2, pp.128-131, January-February-2017.