Geometrical Endmember Extraction and Linear Spectral Unmixing of Multispectral Image
نویسنده
چکیده
Accurate mapping is prepared using Linear unmixing of satellite images. Endmember extraction contributes the unmixing accuracy. In this paper, Endmembers are extracted using different Geometrical algorithms like Pixel Purity Index (PPI), Nearest Finder (N-FINDR) and Sequential Maximum Angle Convex Cone (SMACC) algorithms. Extracted Endmembers are given as input for unmixing and it is attempted using Linear mixing model. Here, Landsat 4-5 Thematic Mapper dataset is tested. Experimental results are compared and it is inferred that SMACC algorithm performs better compared to the PPI and NFINDR algorithm. PPI shows less performance in determining the endmember that are less contributed in a pixel.
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تاریخ انتشار 2016