Multispectrals images segmentation based on DWT and decisions fusion

This paper aims to present a supervised segmentation algorithm based on data fusion for the textured image. The feature extraction method that is used for segmentation is Discrete Wavelet Transform (DWT). In the stage of segmentation, the estimated feature vector of each pixel is sent to Support Vector Machine classifier for an initial labelling. To obtain a more accurate result of segmentation, we integrated a high-level data fusion by combining decisions made by the same classifier. Finally, the performance of the proposed segmentation algorithm is demonstrated on a variety of images.