Thursday 28th of March 2024
 

Soft Computing Techniques for Change Detection in remotely sensed images : A Review


Madhu Khurana and Vikas Saxena

With the advent of remote sensing satellites, a huge repository of remotely sensed images is available. Change detection in remotely sensed images has been an active research area as it helps us understand the transitions that are taking place on the Earths surface . This paper discusses the methods and their classifications proposed by various researchers for change detection. Since use of soft computing based techniques are now very popular among research community, this paper also presents a classification based on learning techniques used in soft-computing methods for change detection.

Keywords: change detection, COP-kmeans, constrained k-means,k-means, fuzzy k-means, ISODATA, Semi supervised SVM, remote sensing, soft-computing, HMRF

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ABOUT THE AUTHORS

Madhu Khurana
Madhu Khurana has done B.Sc(Comp.Sc) from HansRaj College, Delhi University in 1990, M.Tech(I.T.) from GGSIPU, Delhi in 2009. Currently pursuing Ph.D from JIIT Noida, India. Worked in various companies from 1990 to 1993. Followed by working as a freelance consultant to various National Banks and Trading companies by providing services for system development and maintenance. Academic experience of 11 years, presently working in ABES Engineering College, Ghaziabad for last 7+ years. . Her research interest area is Digital Image Processing and Soft Computing

Vikas Saxena
Vikas Saxena is Associate professor in Dept of CSE&IT at JIIT, Noida. He has more than 12 years of experience in academics. His research interest areas are--DIP, Computer vision and Watermarking. He has more than 40 research paper published in repute international jounals and conferences.


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