Results 31 to 40 of about 3,939 (225)

Hyperspectral Unmixing Using Transformer Network

IEEE Transactions on Geoscience and Remote Sensing, 2022
Currently, this paper is under review in IEEE. Transformers have intrigued the vision research community with their state-of-the-art performance in natural language processing. With their superior performance, transformers have found their way in the field of hyperspectral image classification and achieved promising results. In this article, we harness
Preetam Ghosh, Swalpa Kumar Roy, Bikram Koirala, Behnood Rasti, Paul Scheunders   +4 more
openaire   +2 more sources

Spectral Unmixing of Hyperspectral Remote Sensing Imagery via Preserving the Intrinsic Structure Invariant

Sensors, 2018
Hyperspectral unmixing, which decomposes mixed pixels into endmembers and corresponding abundance maps of endmembers, has obtained much attention in recent decades. Most spectral unmixing algorithms based on non-negative matrix factorization (NMF) do not
Yang Shao, Jinhui Lan, Yuzhen Zhang, Jinlin Zou   +3 more
doaj   +1 more source

A Supervised Method for Nonlinear Hyperspectral Unmixing [PDF]

Remote Sensing, 2019
Due to the complex interaction of light with the Earth’s surface, reflectance spectra can be described as highly nonlinear mixtures of the reflectances of the material constituents occurring in a given resolution cell of hyperspectral data. Our aim is to estimate the fractional abundance maps of the materials from the nonlinear hyperspectral data.
Bikram Koirala, Mahdi Khodadadzadeh, Cecilia Contreras, Zohreh Zahiri, Richard Gloaguen, Paul Scheunders   +5 more
openaire   +4 more sources

Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Hyperspectral unmixing has been an important technique that estimates a set of endmembers and their corresponding abundances from a hyperspectral image (HSI).
Xin-Ru Feng, Heng-Chao Li, Rui Wang, Qian Du, Xiuping Jia, Antonio Plaza   +5 more
doaj   +1 more source

Hyperspectral Images Unmixing Based on Abundance Constrained Multi-Layer KNMF

IEEE Access, 2021
Due to the low spatial resolution of the sensors, the hyperspectral images contain mixed pixels. The purpose of hyperspectral unmixing is to decompose the mixed pixels into a series of endmembers and abundance fractions.
Jing Liu, You Zhang, Yi Liu, Caihong Mu
doaj   +1 more source

ADVANCES IN HYPERSPECTRAL AND MULTISPECTRAL IMAGE FUSION AND SPECTRAL UNMIXING [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015
In this work, we jointly process high spectral and high geometric resolution images and exploit their synergies to (a) generate a fused image of high spectral and geometric resolution; and (b) improve (linear) spectral unmixing of hyperspectral ...
C. Lanaras, E. Baltsavias, K. Schindler
doaj   +1 more source

An Overview on Linear Unmixing of Hyperspectral Data [PDF]

Mathematical Problems in Engineering, 2020
Hyperspectral remote sensing technology has a strong capability for ground object detection due to the low spatial resolution of hyperspectral imaging spectrometers. A single pixel that leads to a hyperspectral remote sensing image usually contains more than one feature coverage type, resulting in a mixed pixel.
Jiaojiao Wei, Xiaofei Wang
openaire   +1 more source

Blind Hyperspectral Unmixing with Enhanced 2DTV Regularization Term

Remote Sensing, 2023
For the problem where the existing hyperspectral unmixing methods do not take full advantage of the correlations and differences between all these bands, resulting in affecting the final unmixing results, we design an enhanced 2DTV (E-2DTV ...
Peng Wang, Xun Shen, Yingying Kong, Xiwang Zhang, Liguo Wang   +4 more
doaj   +1 more source

Pixel-Level and Global Similarity-Based Adversarial Autoencoder Network for Hyperspectral Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral unmixing is a critical task in remote sensing, enabling the decomposition of hyperspectral data into their constituent endmembers and abundances.
Wei Tao, Haiyang Zhang, Shan Zeng, Long Wang, Chaoxian Liu, Bing Li   +5 more
doaj   +1 more source

Hyperspectral Unmixing Network Accounting for Spectral Variability Based on a Modified Scaled and a Perturbed Linear Mixing Model

Remote Sensing, 2023
Spectral unmixing is one of the prime topics in hyperspectral image analysis, as images often contain multiple sources of spectra. Spectral variability is one of the key factors affecting unmixing accuracy, since spectral signatures are affected by ...
Ying Cheng, Liaoying Zhao, Shuhan Chen, Xiaorun Li   +3 more
doaj   +1 more source