In this paper, a new multicriterion segmentation method has been proposed to be applied to satellite image of very high spatial resolution (VHSR). It is consisted of the following process: For each region of the grayscale image, a center of gravity has been calculated and it has been also selected a threshold for its histogram. According to a certain criteria, this approach has been based on the separation of the different classes of grayscale in an optimal way. The proposed approach has been tested on synthetic images, and then has applied to an urban environment for the classification of data in Quickbird images. The selected zone of study has been laid in Skhirate-Témara province, northwest of Morocco. Which is based on the Levine and Nazif criterion, this segmentation technique has given promising results compared those obtained using OTSU and K-means methods.

In this paper, we present a new two-dimensional (2D) histogram technique for colour image segmentation using HSV (hue, saturation, and value) colour space. The approach is achieved into two main steps. In the first one, we build a 2D histogram according to a predefined threshold function derived from properties of HSV and the change of the pixel values in a block of 363 neighbouring pixels. In the second one, we use a hierarchical analysis of 2D histogram for detecting the classes, and we perform the segmentation algorithm by reclassification of the pixels not classified in the determined classes, according to Euclidian distance. The method has been applied on synthetic images and reel images devoted to agriculture application. This segmentation technique gives promising results compared with those obtained either by 1D histogram using HSV or 2D histogram using RGB space.

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