Multiple Characteristics Similarity Metric Method for Hyperspectral Image Classification
نویسندگان
چکیده
منابع مشابه
A Classification Based Similarity Metric for 3D Image Retrieval
We present a principled method of obtaining a weighted similarity metric for 3D image retrieval, rmly rooted in Bayes decision theory. The basic idea is to determine a set of most discriminative features by evaluating how well they perform on the task of classifying images according to predeened semantic categories. We propose this indirect method as a rigorous way to solve the diicult feature ...
متن کاملMultiple Classifier Ensembles with Band Clustering for Hyperspectral Image Classification
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 کاملMultiple Classifiers and Graph Cut Method for Spectral Spatial Classification of Hyperspectral Image
Hyperspectral image contains fine spectral and spatial resolutions for generating accurate land use and land cover maps. Supervised classification is the one of method used to exploit the information from the hyperspectral image. The traditional supervised classification methods could not be able to overcome the limitations of the hyperspectral image. The multiple classifier system (MCS) has th...
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
متن کاملHyperspectral Image Classification by Fusion of Multiple Classifiers
Hyperspectral image mostly have very large amounts of data which makes the computational cost and subsequent classification task a difficult issue. Firstly, to solve the problem of computational complexity, spectral clustering algorithm is imported to select efficient bands for subsequent classification task. Secondly, due to lack of labeled training sample points, this paper proposes a new alg...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2020
ISSN: 2169-3536
DOI: 10.1109/access.2020.2964051