Identification of Volcano Hotspots in Multi Spectral ASTER Satellite Images usingDTCWT Image Fusion and ANFIS Classifier
Journal Title: American journal of Engineering Research - Year 2016, Vol 5, Issue 12
Abstract
Volcanic hotspots identification and monitoring can play crucial role in planning and extraction of disaster management. Satellite images have become able alive in this crucial domain to help in the identification of volcano hotspots. This research work aims to implement an automated volcanic hotspots detection approach using Adaptive Neuro Fuzzy Inference System (ANFIS)classifier. In order to improve classification accuracy and performance, a Dual Tree Complex Wavelet Transform (DTCWT) has been employed to fuse the volcano images in different spectrums visible and visible near infrared. The fused images subsequently used for extraction of features with help of Discrete Wavelet Transform (DWT) and Principle Component Analysis (PCA). ANFIS classifier takes these features as input and delivers classification in the way of indicating the possible absence and presence of volcano in that particular image. The approach is validated with help of ASTER volcanic data base, the classifier performance has been evaluated for computing different performance measures. The results demonstrate the improved accuracy that can be brought out by using fused images in the identification of volcano hotspots.
Authors and Affiliations
Mr. S. Muni Rathnam1,, Dr. T. Ramashri,
Keywords
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