کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7153715 1462488 2018 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Spectral-spatial target detection based on data field modeling for hyperspectral data
ترجمه فارسی عنوان
تشخیص هدف طیفی-فضایی براساس مدل سازی اطلاعات داده ها برای داده های هیپرپرترول
کلمات کلیدی
مدل سازی داده ها، استخراج ویژگی، داده های بیشینه طیفی-فضایی، تشخیص هدف،
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی هوافضا
چکیده انگلیسی
Target detection is always an important application in hyperspectral image processing field. In this paper, a spectral-spatial target detection algorithm for hyperspectral data is proposed. The spatial feature and spectral feature were unified based on the data filed theory and extracted by weighted manifold embedding. The novelties of the proposed method lie in two aspects. One is the way in which the spatial features and spectral features were fused as a new feature based on the data field theory, and the other is that local information was introduced to describe the decision boundary and explore the discriminative features for target detection. The extracted features based on data field modeling and manifold embedding techniques were considered for a target detection task. Three standard hyperspectral datasets were considered in the analysis. The effectiveness of the proposed target detection algorithm based on data field theory was proved by the higher detection rates with lower False Alarm Rates (FARs) with respect to those achieved by conventional hyperspectral target detectors.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chinese Journal of Aeronautics - Volume 31, Issue 4, April 2018, Pages 795-805
نویسندگان
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