Fuzzy min-max neural network for satellite infrared image clustering
Barnali Goswami, Gupinath Bhandari, Sanjay Goswami · 2012
The process of estimation of precipitation from satellite images begins with the detection and identification of convective clouds. Clustering of the satellite infrared images is required in order to estimate the cloud cover area. In this paper a neuro-fuzzy technique in the form of unsupervised fuzzy minmax clustering neural (FMMCN) network has been implemented for clustering satellite infrared image. Each cluster is in the form of an n-dimensional hyperbox defined by minimum and maximum points and a fuzzy membership function. FMMCN suits this application area because it is completely unsupervised and hence, unlabeled data can be used with it. Also the number of clusters is not required to be mentioned at the beginning as it is calculated dynamically.