Abstract—In recent years, the image processing intelligent based systems has been the subject of interest for many researchers. In this manner, interpretation of urban aerial hyperspectral textured images is lionizing due to special features of this images. Image segmentation is the first step to reach this aim and extract features of these images. The correct selection of spectral bands is very important, because of multiplicity of spectral bands in this images and variety of texture in each of spectral bands. Since not all spectral bands include useful information, taking into account all of spectral bands decreases the speed of processing and accuracy of segmentation. In this paper, several dimension reduction or in other words spectral band reduction approach studied. In addition, the effect of each dimension reduction algorithms on accuracy of segmentation represented.
Index Terms—Hyperspectral image, dimension reduction, extended mathematical morphology, region growing.
Ali Bakhshi is with the Electrical Engineering Department, Shahrood Branch, Islamic Azad University, Shahrood, Iran (e-mail: firstname.lastname@example.org).
Mohammad Hassan Ghassemian is with the Electrical Engineering Department, Tarbiat Modares University, Tehran, Iran (e-mail: email@example.com).
Alireza Ahmadifard is with the Electrical Engineering Department, Shahrood University of Technology, Shahrood, Iran (e-mail: firstname.lastname@example.org).
Cite: Ali Bakhshi, Mohammad Hassan Ghassemian, and Alireza Ahmadifard, "The Effect of the Spectral Band Selection Method on Hyperspectral Images Segmentation Accuracy," International Journal of Computer Theory and Engineering vol. 4, no. 3, pp. 318-321, 2012.