Ensemble EMD-Based Spectral-Spatial Feature Extraction for Hyperspectral Image Classification
نویسندگان
چکیده
منابع مشابه
Spectral-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 کاملBidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image Classification
This paper proposes a novel deep learning framework named bidirectional-convolutional long short term memory (Bi-CLSTM) network to automatically learn the spectral-spatial feature from hyperspectral images (HSIs). In the network, the issue of spectral feature extraction is considered as a sequence learning problem, and a recurrent connection operator across the spectral domain is used to addres...
متن کاملHyperspectral Image Classification Based on Nonlinear Spectral-Spatial Network
Recently, for the task of hyperspectral images classification, deep learning-based methods have revealed promising performance. However, the complex network structure and time-consuming training process have restricted their applications. In this letter, we construct a much simpler network, nonlinear spectral-spatial network (NSSNet), for hyperspectral images classification. NSSNet is developed...
متن کاملMulti-view feature extraction for hyperspectral image classification
We study the multi-view feature extraction (MV-FE) framework for the classification of hyperspectral images acquired from airborne and spaceborne sensors. This type of data is naturally composed by distinct blocks of spectral channels, forming the hypercube. To reduce the dimensionality of the data by taking advantage of this particular structure, an unsupervised multi-view feature extraction m...
متن کاملNonparametric Fuzzy Feature Extraction for Hyperspectral Image Classification
Feature extraction plays an essential role in high-dimensional data classification. Linear discriminant analysis (LDA) is one of the most well-known methods for reducing data dimensionality in various fields. However, there are three inherent limitations when applying LDA to extract features. First, the number of features that can be extracted by LDA is the number of classes minus one at most. ...
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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing
سال: 2020
ISSN: 1939-1404,2151-1535
DOI: 10.1109/jstars.2020.3018710