کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6951885 1451707 2018 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Dictionary-aided hyperspectral unmixing based on constrained l2,q-l2,p optimization
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
پیش نمایش صفحه اول مقاله
Dictionary-aided hyperspectral unmixing based on constrained l2,q-l2,p optimization
چکیده انگلیسی
Dictionary-aided unmixing has been introduced as a semi-supervised unmixing method, under the assumption that the observed mixed pixel of a hyperspectral image can be expressed in the form of different linear combinations of a few spectral signatures from an available spectral library. Sparse-regression-based unmixing methods have been recently proposed to solve this problem. Mostly, lp-norm minimization is a closer surrogate to the l0-norm minimization and can be solved more efficiently than l1-norm minimization. In this paper, we model the hyperspectral unmixing as a constrained l2,q-l2,p optimization problem. To effectively solve the induced optimization problems for any q (1≤q≤2) and p (0
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Digital Signal Processing - Volume 73, February 2018, Pages 117-127
نویسندگان
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