Hyperspectral Image Classification Using Graph Clustering Methods
نویسندگان
چکیده
منابع مشابه
Hyperspectral Image Classification Using Graph Clustering Methods
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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Due to the high dimensionality of a hyperspectral image, classification accuracy of a single classifier may be limited when the size of the training set is small. A divide-and-conquer approach has been proposed, where a classifier is applied to each group of bands and the final output will be the fused result of multiple classifiers. Since the dimensionality in each band group is much lower, cl...
متن کاملHyperspectral Image Classification
Article history: Received 12 October 2014 Received in revised form 26 December 2014 Accepted 1 January 2015 Available online 25 February 2015
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For Hyperspectral image (HSI) datasets, each class have their salient feature and classifiers classify HSI datasets according to the class's saliency features, however, there will be different salient features when use different normalization method. In this letter, we report the effect on classifiers by different normalization methods and recommend the best normalization methods for classifier...
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ژورنال
عنوان ژورنال: Image Processing On Line
سال: 2017
ISSN: 2105-1232
DOI: 10.5201/ipol.2017.204