A New Methodology for Spectral-Spatial Classification of Hyperspectral Images
نویسندگان
چکیده
منابع مشابه
Spectral-spatial classification of hyperspectral images by combining hierarchical and marker-based Minimum Spanning Forest algorithms
Many researches have demonstrated that the spatial information can play an important role in the classification of hyperspectral imagery. This study proposes a modified spectral–spatial classification approach for improving the spectral–spatial classification of hyperspectral images. In the proposed method ten spatial/texture features, using mean, standard deviation, contrast, homogeneity, corr...
متن کاملHyperspectral Images Classification by Combination of Spatial Features Based on Local Surface Fitting and Spectral Features
Hyperspectral sensors are important tools in monitoring the phenomena of the Earth due to the acquisition of a large number of spectral bands. Hyperspectral image classification is one of the most important fields of hyperspectral data processing, and so far there have been many attempts to increase its accuracy. Spatial features are important due to their ability to increase classification acc...
متن کاملSpectral-Spatial Response for Hyperspectral Image Classification
This paper presents a hierarchical deep framework called Spectral-Spatial Response (SSR) to jointly learn spectral and spatial features of Hyperspectral Images (HSIs) by iteratively abstracting neighboring regions. SSR forms a deep architecture and is able to learn discriminative spectral-spatial features of the input HSI at different scales. It includes several existing spectral-spatial-based ...
متن کاملA Comparison Study of Different Marker Selection Methods for Spectral-spatial Classification of Hyperspectral Images
An effective approach based on the Minimum Spanning Forest (MSF), grown from automatically selected markers using Support Vector Machines (SVM), has been proposed for spectral-spatial classification of hyperspectral images by Tarabalka et al. This paper aims at improving this approach by using image segmentation to integrate the spatial information into marker selection process. In this study, ...
متن کاملA Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images
Classification of hyperspectral images always suffers from high dimensionality and very limited labeled samples. Recently, the spectral-spatial classification has attracted considerable attention and can achieve higher classification accuracy and smoother classification maps. In this paper, a novel spectral-spatial classification method for hyperspectral images by using kernel methods is invest...
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: Journal of Sensors
سال: 2016
ISSN: 1687-725X,1687-7268
DOI: 10.1155/2016/1538973