Hyperspectral Image Segmentation Method Based on Region Active Contour
基于区域活动轮廓模型的高光谱图像分割方法

Considering the characteristic of hyperspectral image,we have proposed a segmentation method based on region active contour.The energy function in Chan-Vese method is improved and both spatial and spectral information are employed.Spatial term of the function is restricted by global spatial information and the consistent intensity in homogeneous region; while spectral term is restricted by the consistent spectrum of target.Finally the image is segmented by minimizing the energy function.This algorithm can extract indistinct contours of hyper- spectral image,and thus reduce the influence caused by mixed pixels and the shadows around the target.Numerical experiments are conducted on AVIRIS data.Results show that this method reaches satisfying effects in performance and adapts to complex scene in some degree.