TY - JOUR JF - jsdp JO - JSDP VL - 13 IS - 3 PY - 2016 Y1 - 2016/12/01 TI - Sparse unmixing of hyper-spectral images using a pruned spectral library TT - تجزیه‌ ی تُنُک تصاویر ابرطیفی با استفاده از یک کتابخانه‌ ی طیفی هرس شده N2 - Spectral unmixing of hyperspectral images is one of the most important research fields in remote sensing. Recently, the direct use of spectral libraries in spectral unmixing is on increase. In this way which is called sparse unmixing, we do not need an endmember extraction algorithm and the number determination of endmembers priori. Since spectral libraries usually contain highly correlated spectra, the sparse unmixing approach leads to non-admissible solutions. On the other hand, most of the proposed solutions are not noise-resistant and do not reach to a sufficiently high sparse solution. In this paper, with the purpose of overcoming the problems above, at first the spectral library will be pruned based on the spectral information of the image,clustering and classification techniques. Then a genetic algorithm will be used for sparse unmixing. The experimental results on the simulated and real images show that the proposed method gives good results in noisy images. SP - 155 EP - 169 AU - Fayyazi, Hossein AU - Dehghani, Hamid AU - Hosseini, Mojtaba AD - Malek-Ashtar University of Technology KW - Hyper-spectral images KW - Spectral Library Pruning KW - Sparse Unmixing. UR - http://jsdp.rcisp.ac.ir/article-1-128-en.html DO - 10.18869/acadpub.jsdp.13.3.155 ER -