In this paper a context sensitive technique for unsupervised change detection in multitemporal images using Pulse coupled neural network is proposed . PCNN is an biologically inspired neural network based on cats visual cortical neurons. The key strength of PCNN model is that it can operate without training and in comparison with more traditional Neural network s it has benefits like signal associated to the PCNN has properties of invariance to changes in rotation ,scale ,translation of an input patterns . This property is very useful when dealing with very high resolution images.

1. Fabio Pacific, Fabio Del Frate "Automatic change detection in very high resolution images with pulse coupled neural networks" IEEE Tran. Geoscience and remote sensing vol. 7 pp. 58-62.
2. Susmitha Ghosh, Lorenzo Bruzzone "A context sensitive technique for unsupervised change detection based on Hopfield type neural networks" IEEE Tran. Geoscience and remote sensing vol. 45 pp. 778-789
3. Swarnajyothi patra ,sushmita Ghosh, Ashish Ghosh "Unsupervised change detection in remote sensing images using one dimensional self-organizing feature map neural network "conference on computing IEEE computer society
4. Swarnajyothi patra ,sushmita Ghosh, Ashish Ghosh "An Unsupervised change detection in remote sensing images using modified self-organizing feature map neural network" conference International journal of approximation reasoning 2009 pp. 37-50
5. Victor mihal " A neural network approach for land cover change detection in multitemporal multispectral remote sensing imagery"recent advances in signal processing ,computional geometry and system theory
6. Image change detection using Gaussian mixture model and genetic algorithm J. Vis. Commun. Image R. 21 (2010) 965–974
7. Book by T. Lindbad and J. M. kinser "image processing using pulse coupled neural networks" springer second edition.
8. Trong -Thuc Hoang, Ngoc-Hung Nguyen, Xuan-Thuan Nguyen and Trong Tu] "A Real-time Image Feature Extraction Using PCNN" International journal of emerging trends and technology in computer science PP
9. Lorenzo Bruzzone, Member, IEEE, and Diego Fernàndez Prieto, Student Member, IEEE, " Automatic Analysis of the Difference Image for Unsupervised Change Detection" IEEE transactions on geoscience and remote sensing, vol. 38, NO. 3, MAY 2000

Pulse-coupled Neural Networks (pcnn) Unsupervised Change Detection And Multitemporal Images.