Spatial analysis of images sensed and captured from a satellite provides less adequate information about a remote location. Hence spectral analysis becomes essential. Hyperspectral image is one of the remotely sensed images, superior to multispectral images in providing spectral information. Target detection is one of the significant requirements in many areas such as military, agriculture etc. Sub pixel target detection, which further divides each pixel of the image into partitions, is possible only with spectral analysis of hyperspectral image. This paper focuses on developing an algorithm for segmenting hyperspectral image using sub pixel target detection followed by Fuzzy C-Means(FCM) clustering technique. Principal Component Analysis (PCA) is the basic step adopted to reduce the high dimensional data of image to low dimensional data. Mixture tuned matched filtering technique is used for sub pixel target detection because it is a combination of linear spectral unmixing and matched filtering and has advantages of both the techniques.
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