Results 281 to 290 of about 11,136 (312)

Mixed Noise Reduction in Hyperspectral Imagery

2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2019
In this paper, a hyperspectral mixed noise reduction technique is proposed called HyMiR. We assume that hyperspectral images include Gaussian and sparse noise types. First, the Gaussian noise is removed using a recently-developed method called hyperspectral restoration (HyRes).
Behnood Rasti, Pedram Ghamisi, Jocelyn Chanussot   +2 more
openaire   +1 more source

Estimate the Number of Endmembers for Hyperspectral Imagery

2009 International Conference on Environmental Science and Information Application Technology, 2009
In practice, the determination of the number of endmembers for hyperspectral images of the areas without priori knowledge is highly difficult. This article brings forward an automatic method, which can estimate the number of endmembers for hyperspectral imagery without priori knowledge of the area, according to the theory of Orthogonal subspace ...
Wei Chen, Xu-chu Yu, He Wang
openaire   +1 more source

Constrained band selection for hyperspectral imagery

IEEE Transactions on Geoscience and Remote Sensing, 2006
Constrained energy minimization (CEM) has shown effective in hyperspectral target detection. It linearly constrains a desired target signature while minimizing interfering effects caused by other unknown signatures. This paper explores this idea for band selection and develops a new approach to band selection, referred to as constrained band selection (
Chein-I Chang, Su Wang 0002
openaire   +1 more source

Unified mixing model for hyperspectral imagery

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015
Multiple mixing models for hyperspectral imagery have been developed over the years. The most common is the linear mixing model which states that each pixel's spectral signature is a linear combination of the unique materials (or endmembers) in the scene.
openaire   +1 more source

Anomaly detection and classification for hyperspectral imagery

IEEE Transactions on Geoscience and Remote Sensing, 2002
Anomaly detection becomes increasingly important in hyperspectral image analysis, since hyperspectral imagers can now uncover many material substances which were previously unresolved by multispectral sensors. Two types of anomaly detection are of interest and considered in this paper. One was previously developed by Reed and Yu to detect targets whose
Chein-I Chang, Shao-Shan Chiang
openaire   +1 more source

Nonlinear mixture analysis for hyperspectral imagery

2009 IEEE International Geoscience and Remote Sensing Symposium, 2009
Nonlinear mixture analysis for hyperspectral imagery is investigated in this paper. A simple but effective nonlinear mixture model is adopted, where the multiplication of each pair of endmembers results in another “endmember”, representing nonlinear scattering effect during pixel construction process.
Nareenart Raksuntorn, Qian Du 0001
openaire   +1 more source

Morphological Band Selection for Hyperspectral Imagery

IEEE Geoscience and Remote Sensing Letters, 2018
In this letter, a novel morphological band selection method is proposed to obtain the most representative bands from hyperspectral image (HSI) in an unsupervised manner. In order to sufficiently process the HSI, we propose to use only a small set of data instead of using the original full data.
Wang, Jingyu, Wang, Xianyu, Zhang, Ke, Madani, Kurosh, Sabourin, Christophe   +4 more
openaire   +1 more source

Anomaly discrimination and classification for hyperspectral imagery

2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2015
Anomaly detection finds data samples whose signatures are spectrally distinct from their surrounding data samples. Unfortunately, it generally cannot discriminate its detected anomalies one from another. One common approach is to measure closeness of spectral characteristics among detected anomalies to determine if the detected anomalies are actually ...
Li-Chien Lee, Drew Paylor, Chein-I Chang
openaire   +1 more source

Toward the Vectorization of Hyperspectral Imagery

IEEE Transactions on Geoscience and Remote Sensing, 2023
Leyuan Fang, Yinglong Yan, Jun Yue 0004, Yue Deng 0001   +3 more
openaire   +1 more source

Separability between pedestrians in hyperspectral imagery

Applied Optics, 2013
The popularity of hyperspectral imaging (HSI) in remote sensing continues to lead to it being adapted in novel ways to overcome challenging imaging problems. This paper reports on research efforts exploring the phenomenology of using HSI as an aid in detecting and tracking human pedestrians.
Jared, Herweg, John, Kerekes, Michael, Eismann   +2 more
openaire   +2 more sources