Water information extraction from remote sensing image using EMD and fraction method

Abstract

This paper presents a model for extracting water from remote sensing by using empirical mode decomposition( EMD) and fractal theory. The authors tried to improve accuracy with spectral information and texture characteristics. Principal component analysis was carried out on the image to obtain the biggest first principal component that contains effective information,then the fractal dimension of each pixel was calculated; at the same time,the first principal component was decomposed with the method of EMD to get the first three empirical mode functions,which,coupled with the original band information,served as the research data. With the method of maximum likelihood classifier,the waters were extracted. This method fully combines the advantages of EMD method in noise reduction and the advantage of fractal theory in texture information extraction. Experiment shows that this method can effectively improve the extraction accuracy,with the Kappa up to 0. 932 5.