Unsupervised Change Detection in Remote-Sensing Images using One-dimensional Self-Organizing Feature Map Neural Network
Abstract
In this paper, we propose an unsupervised change- detection technique based on self-organizing feature map neural network that discriminates the "difference image" by constructing two clusters. In the proposed network, the number of input neurons is equal to the dimension of the input pattern while the number of output neurons is two. To confirm the effectiveness of the proposed technique a comparative study is made with another existing context- sensitive technique.
Authors: Swarnajyoti Patra, Susmita Ghosh, Ashish Kumar Ghosh