Remote sensing image texture enhancement based on HSV-BEMD algorithm
Min Ma, Guoao Feng · 2019
Remote sensing image texture feature is of great importance, especially used in geological mapping and tectonic interpretation. In this paper, HSV algorithm is used to transform a multi-band color image into HSV colorspace, texture feature in the brightness component V and a panchromatic image is extracted by bi-dimensional empirical mode decomposition (BEMD), in which radial basis function(RBF) interpolation is used to fit the envelops. As the texture feature of high frequency usually exists in the first IMF, the summation of their first IMF and the panchromatic image is taken as a substitute for the brightness component V, then the enhanced color image is obtained by HSV inverse transformation. Compared with other texture enhancement algorithms like Canny and wavelet transform, objectively evaluated by variance, Shannon information, average gradient and spatial frequency, the algorithm in this paper is proved effective in multi-band color image texture enhancement with panchromatic band. The whole process is executed on MATLAB2010b platform self-adaptively.