Hyperspectral Image Segmentation Using Seed Points and Minimum Path Estimation Method

In hyper spectral images, segmentation as preprocess has high importance. In this paper, in two stages, the process of segmentation is done by considering spectrum of pixel in all bands. In the first stage, the image is turned to some sub zones by use of flatting zone method, and then a more complete segmentation is done by use of estimation method of minimum path on zones. The suggested method produces new segmentation by use of appropriate choice of seeds and by considering minimum path of pixel to the seeds. The suggested method is implemented on AVIRIS image and produces more ideal number of zones and borders in compare with the other method.