Results 31 to 40 of about 7,130 (165)

Feature Extraction Based Multi-Structure Manifold Embedding for Hyperspectral Remote Sensing Image Classification

IEEE Access, 2017
Hyperspectral remote sensing image is a typical high-dimensional data with a large number of redundant information, which will impact the classification accuracy.
Yuhang Gan, Fulin Luo, Juhua Liu, Bing Lei, Tao Zhang, Ke Liu   +5 more
doaj   +1 more source

Classification of hyperspectral images via improved cycle‐MLP

IET Computer Vision, 2022
Pixel‐wise classification of hyperspectral image (HSI) is a hot spot in the field of remote sensing. The classification of HSI requires the model to be more sensitive to dense features, which is quite different from the modelling requirements of ...
Na Gong, Chunlei Zhang, Heng Zhou, Kai Zhang, Zhongyuan Wu, Xin Zhang   +5 more
doaj   +1 more source

Mapping Coastal Wetlands Using Transformer in Transformer Deep Network on China ZY1-02D Hyperspectral Satellite Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Coastal wetlands mapping is a big challenge in remote sensing fields because of similar spectrum of different ground objects and their severe fragmentation and spatial heterogeneity.
Kai Liu, Weiwei Sun, Yijun Shao, Weiwei Liu, Gang Yang, Xiangchao Meng, Jiangtao Peng, Dehua Mao, Kai Ren   +8 more
doaj   +1 more source

Land use/land cover (LULC) classification using hyperspectral images: a review

Geo-spatial Information Science
In the rapidly evolving realm of remote sensing technology, the classification of Hyperspectral Images (HSIs) is a pivotal yet formidable task. Hindered by inherent limitations in hyperspectral imaging, enhancing the accuracy and efficiency of HSI ...
Chen Lou, Mohammed A. A. Al-qaness, Dalal AL-Alimi, Abdelghani Dahou, Mohamed Abd Elaziz, Laith Abualigah, Ahmed A. Ewees   +6 more
doaj   +1 more source

Semi-Supervised Classification for Hyperspectral Images Based on Multiple Classifiers and Relaxation Strategy

ISPRS International Journal of Geo-Information, 2018
Hyperspectral image (HSI) classification is a fundamental and challenging problem in remote sensing and its various applications. However, it is difficult to perfectly classify remotely sensed hyperspectral data by directly using classification ...
Fuding Xie, Dongcui Hu, Fangfei Li, Jun Yang, Deshan Liu   +4 more
doaj   +1 more source

Programmable Spectrometry -- Per-pixel Classification of Materials using Learned Spectral Filters

, 2019
Many materials have distinct spectral profiles. This facilitates estimation of the material composition of a scene at each pixel by first acquiring its hyperspectral image, and subsequently filtering it using a bank of spectral profiles.
Sankaranarayanan, Aswin C., Saragadam, Vishwanath   +1 more
core   +1 more source

Hyperspectral image classification on insufficient-sample and feature learning using deep neural networks: A review

International Journal of Applied Earth Observations and Geoinformation, 2021
Over the years, advances in sensor technologies have enhanced spatial, temporal, spectral, and radiometric resolutions, thus significantly improving the size, resolution, and quality of imagery.
Naftaly Wambugu, Yiping Chen, Zhenlong Xiao, Kun Tan, Mingqiang Wei, Xiaoxue Liu, Jonathan Li   +6 more
doaj   +1 more source

Spectral Segmentation Multi-Scale Feature Extraction Residual Networks for Hyperspectral Image Classification

Remote Sensing, 2023
Hyperspectral image (HSI) classification is a vital task in hyperspectral image processing and applications. Convolutional neural networks (CNN) are becoming an effective approach for categorizing hyperspectral remote sensing images as deep learning ...
Jiamei Wang, Jiansi Ren, Yinbin Peng, Meilin Shi   +3 more
doaj   +1 more source

Spectral Swin Transformer Network for Hyperspectral Image Classification

Remote Sensing, 2023
Hyperspectral images are complex images that contain more spectral dimension information than ordinary images. An increasing number of HSI classification methods are using deep learning techniques to process three-dimensional data. The Vision Transformer
Baisen Liu, Yuanjia Liu, Wulin Zhang, Yiran Tian, Weili Kong   +4 more
doaj   +1 more source

Task-Driven Dictionary Learning for Hyperspectral Image Classification with Structured Sparsity Constraints

, 2015
Sparse representation models a signal as a linear combination of a small number of dictionary atoms. As a generative model, it requires the dictionary to be highly redundant in order to ensure both a stable high sparsity level and a low reconstruction ...
Nasrabadi, Nasser M., Sun, Xiaoxia, Tran, Trac D.   +2 more
core   +1 more source