Improved N-FINDR Hyper-spectral Member Extraction Algorithm Based on Pure Pixel Index

doi:10.13474/j.cnki.11-2246.2018.0050

Abstract

Abstract:

In order to solve the low accuracy problem of the quantitative interpretation of remote sensing images caused by mixed pixels,two different mixed pixel extraction algorithms are analyzed and compared in this paper.In consideration of the pure pixel index exponential algorithm efficiency greatly reduces as the number of iterations increases and the random choice of classical N-FINDR algorithm's element will lead to different accuracy of the solution,an improved N-FINDR algorithm based on pure pixel index is proposed.Relative to the traditional N-FINDR algorithm,the improved N-FINDR algorithm can construct the candidate element and obtain the optimal solution more efficiently.Synthesize the characteristics of hyper-spectral image data,first,the improved N-FINDR algorithm uses the pure pixel index to calculate the number of alternate port elements,and then use the classical N-FINDR algorithm to solve the maximal single-body vertex,then use the pure element completes the abundance inversion.Finally,the algorithm is verified by the air-calibrated airborne hyper-spectral data Cup95eff.int in the ENVI products.The experimental results show that the improved N-FINDR algorithm is more efficiently than the traditional N-FINDR algorithm in the aspect of endmember extraction.

Key words: hyper-spectral remote sensing, unmixing pixel, endmember extraction algorithm

CLC Number:

P237

YANG Pengfei, LIAO Xiuying, XU Qiheng, CHENG Hui. Improved N-FINDR Hyper-spectral Member Extraction Algorithm Based on Pure Pixel Index[J]. 测绘通报, 2018, 0(2): 89-93.

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