Results 51 to 60 of about 11,517,403 (217)

Hyperspectral and Multispectral Data Fusion via Joint Local-Nonlocal Modeling and Truncation Operator

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Fusion technology has been the core strategy to obtain a high-spatial-spectral resolution hyperspectral image (HSI). In recent years, few fusion models focused on exploiting the underlying manifold structure in the spatial dimension of the high ...
Jiawei Jiang, Yuchao Feng, Honghui Xu, Guojiang Shen, Jianwei Zheng   +4 more
doaj   +1 more source

Domain Transfer Learning for Hyperspectral Image Super-Resolution [PDF]

, 2019
A Hyperspectral Image (HSI) contains a great number of spectral bands for each pixel; however, the spatial resolution of HSI is low. Hyperspectral image super-resolution is effective to enhance the spatial resolution while preserving the high-spectral ...
Zhang, LF, Lefei Zhang, Jane You, Li, XY, You, JN, Xiaoyan Li   +5 more
core   +1 more source

SBHSR: single-band super-resolution method for hyperspectral images based on blind degradation and fusion of auxiliary band

Geocarto International
Despite natural image super-resolution (SR) methods have achieved great success, super-resolution methods for hyperspectral image (HSI) with rich spectral features are still a very challenging task.
Lijing Bu, Xi Xiao, Zhengpeng Zhang, Deng Mingjun   +3 more
doaj   +1 more source

Correlation Matrix-Based Fusion of Hyperspectral and Multispectral Images

Remote Sensing, 2023
The fusion of the hyperspectral image (HSI) and the multispectral image (MSI) is commonly employed to obtain a high spatial resolution hyperspectral image (HR-HSI); however, existing methods often involve complex feature extraction and optimization steps,
Hong Lin, Jun Li, Yuanxi Peng, Tong Zhou, Jian Long, Jialin Gui   +5 more
doaj   +1 more source

Quality criteria benchmark for hyperspectral imagery [PDF]

, 2005
Hyperspectral data appear to be of a growing interest over the past few years. However, applications for hyperspectral data are still in their infancy as handling the significant size of the data presents a challenge for the user community.
Christophe, Emmanuel, Léger, Dominique, Mailhes, Corinne   +2 more
core   +1 more source

WHU-OHS: A benchmark dataset for large-scale Hersepctral Image classification

International Journal of Applied Earth Observations and Geoinformation, 2022
Hyperspectral image (HSI) classification is one of the most important remote sensing techniques. Currently, the performances of most of the HSI classification networks on the public HSI datasets are overoptimistic (i.e., the overall accuracy exceeds 98 %)
Jiayi Li, Xin Huang, Lilin Tu
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

UC Food Waste: A Multimodal Robotic Perception Dataset for Robust Contaminant Detection in Complex Biowaste Scenes

Advanced Robotics Research, EarlyView.
A balanced multimodal food‐waste dataset and a novel Split Spatial‐Spectral Attention fusion framework are presented for robotic contaminant detection. Separate processing of RGB, thermal, and multispectral inputs preserves subtle material signatures before feature integration, reducing modality interference and improving classification and ...
Matthew Vestal, James Ireland, David Hinwood, Xing Wang, Min Wang, Damith Herath   +5 more
wiley   +1 more source

Fusing Spatial Attention with Spectral-Channel Attention Mechanism for Hyperspectral Image Classification via Encoder–Decoder Networks

Remote Sensing, 2022
In recent years, convolutional neural networks (CNNs) have been widely used in hyperspectral image (HSI) classification. However, feature extraction on hyperspectral data still faces numerous challenges.
Jun Sun, Junbo Zhang, Xuesong Gao, Mantao Wang, Dinghua Ou, Xiaobo Wu, Dejun Zhang   +6 more
doaj   +1 more source

Exploring Chromatic Aberration and Defocus Blur for Relative Depth Estimation from Monocular Hyperspectral Image

, 2021
This article investigates spectral chromatic and spatial defocus aberration in a monocular hyperspectral image (HSI) and proposes methods on how these cues can be utilized for relative depth estimation. The main aim of this work is to develop a framework
Gao, Y, Zia, A, Zhou, J, Jun Zhou, Ali Zia, Yongsheng Gao   +5 more
core   +1 more source