Meta-XGBoost for Hyperspectral Image Classification Using Extended MSER-Guided Morphological Profiles
نویسندگان
چکیده
منابع مشابه
A new approach to mixed pixel classification of hyperspectral imagery based on extended morphological profiles
This paper presents a new approach to the analysis of hyperspectral images, a new class of image data that is mainly used in remote sensing applications. The method is based on the generalization of concepts from mathematical morphology to multi-channel imagery. A new vector organization scheme is described, and fundamental morphological vector operations are de#ned by extension. Theoretical de...
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Hyperspectral imagery is a challenging modality due to the dimension of the pixels which can range from hundreds to over a thousand frequencies depending on the sensor. Most methods in the literature reduce the dimension of the data using a method such as principal component analysis, however this procedure can lose information. More recently methods have been developed to address classificatio...
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Hyperspectral remote sensing increases the detectability of pixeland subpixel-sized targets by exploiting the finer detail in the spectral signatures. In this paper, we describe a new unsupervised algorithm for the detection of both full pixel and mixed pixel targets in hyperspectral imagery. The proposed method automatically resolves targets by using extended mathematical morphology operations...
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2020
ISSN: 2072-4292
DOI: 10.3390/rs12121973