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دانلود مقاله Comparison and evaluation between several spectral based endmember extraction algorithms on real hyperspectral remotely sensed images فایل ورد (word) دارای 7 صفحه می باشد و دارای تنظیمات در microsoft word می باشد و آماده پرینت یا چاپ است

فایل ورد دانلود مقاله Comparison and evaluation between several spectral based endmember extraction algorithms on real hyperspectral remotely sensed images فایل ورد (word) کاملا فرمت بندی و تنظیم شده در استاندارد دانشگاه و مراکز دولتی می باشد.

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توجه : در صورت  مشاهده  بهم ریختگی احتمالی در متون زیر ،دلیل ان کپی کردن این مطالب از داخل فایل ورد می باشد و در فایل اصلی دانلود مقاله Comparison and evaluation between several spectral based endmember extraction algorithms on real hyperspectral remotely sensed images فایل ورد (word) ،به هیچ وجه بهم ریختگی وجود ندارد

بخشی از متن دانلود مقاله Comparison and evaluation between several spectral based endmember extraction algorithms on real hyperspectral remotely sensed images فایل ورد (word) :

سال انتشار: 1393
محل انتشار: اولین کنفرانس ملی کامپیوتر، فن آوری اطلاعات و ارتباطات
تعداد صفحات: 7
نویسنده(ها):
Fatemeh Kowkabi – EE Department, Faculty member of Marvdasht Islamic Azad University, Marvdasht, Iran

چکیده:

Mixing constituent elements at the pixel level occurs as the result of insufficient spatial resolution in hyperspectral images. Extraction of spectral signatures of such constituent elements which are known as endmembers in each mixed pixel and estimating the abundance maps of such pure spectral signatures are two important roles in Spectral Mixture Analysis(SMA). Most of algorithms, which was proposed for endmember extraction, are relayed on only spectral information such as OSP,N-Finder,VCA,PPI,IEA, SGA without considering spatial arrangement and distribution of image pixels. We review these algorithms and compare them from the view points of RMSE and processing time, on two real hyperspectral Aviris Cuprite and Indian Pines scenes. We demonstrated that VCA results the best response to RMSE of reconstructed original image and processing time in comparison with others.

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