A batch-wise segmentation algorithm for hyperspectral images

The aim of segmentation is to partition the image into a set of adjacent homogeneous regions. Most of existing hyperspectral imagery (HSI) segmentation approaches were designed to assign each pixel to one of the regions. However, due to the low-spatial-resolution, pixel mixing presents a challenge for HSI segmentation because a mixed spectrum does not correspond to any single well-defined material. As a result, it is difficult to determine which region the mixed pixels belong to. To address such problem, we proposed a batch-wise segmentation algorithm for HSI. First, pure pixels and mixed pixels in the HSI are separated. Then, those pure pixels are grouped into different regions. Finally, the mixed pixels are determined by its spatial neighboring pure pixels. Experimental results on a real HSI data indicate that the proposed algorithm provides more accurate segmentation maps, when compared to the traditional segmentation techniques.