Results 11 to 20 of about 45,417 (317)

Hyperspectral Data: Efficient and Secure Transmission [PDF]

Algorithms, 2017
Airborne and spaceborne hyperspectral sensors collect information which is derived from the electromagnetic spectrum of an observed area. Hyperspectral data are used in several studies and they are an important aid in different real-life applications (e.g., mining and geology applications, ecology, surveillance, etc.). A hyperspectral image has a three-
Pizzolante, Raffaele, Carpentieri, Bruno
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Hyperspectral IASI L1C Data Compression [PDF]

Sensors, 2017
The Infrared Atmospheric Sounding Interferometer (IASI), implemented on the MetOp satellite series, represents a significant step forward in atmospheric forecast and weather understanding. The instrument provides infrared soundings of unprecedented accuracy and spectral resolution to derive humidity and atmospheric temperature profiles, as well as some
Joaquin Garcia-Sobrino, Joan Serra-Sagristà, Joan Bartrina-Rapesta   +2 more
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Power spectral clustering on hyperspectral data [PDF]

2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
Classification of remotely sensed data is an important task for many practical applications. However, it is not always possible to get the ground truth for supervised learning methods. Thus unsupervised methods form a valuable tool in such situations. Such methods are referred to as clustering methods. There exists several strategies for clustering the
Challa, Aditya, Danda, Sravan, Daya Sagar, B S, Najman, Laurent   +3 more
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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

Hyperspectral Data Augmentation

CoRR, 2019
Submitted to IEEE Geoscience and Remote Sensing ...
Jakub Nalepa, Michal Myller, Michal Kawulok   +2 more
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Fuzzy spectral and spatial feature integration for classification of nonferrous materials in hyperspectral data [PDF]

, 2009
Hyperspectral data allows the construction of more elaborate models to sample the properties of the nonferrous materials than the standard RGB color representation.
Iriondo, Pedro M., Ghita, Ovidiu, Whelan, PF, Picon, Artzai, Whelan, Paul F.   +4 more
core   +1 more source

Implementation strategies for hyperspectral unmixing using Bayesian source separation. [PDF]

, 2010
Positive Source Separation (BPSS) is a useful unsupervised approach for hyperspectral data unmixing, where numerical non-negativity of spectra and abundances has to be ensured, such in remote sensing. Moreover, it is sensible to impose a sum-to-one (full
Moussaoui, Saïd, Schmidt, Albrecht, Tréguier, Erwan, Maël Guiheneuf, Guiheneuf, Maël, Saïd Moussaoui, Erwan Treguier, Albrecht Schmidt, Nicolas Dobigeon, Dobigeon, Nicolas, Frédéric Schmidt, Schmidt, Frédéric   +11 more
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Informational Clustering of Hyperspectral Data

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014
Hyperspectral remote sensing is recognized as a powerful tool for mineralogical mapping of exposed surfaces on Earth and planets, as well. It allows for more rigorous discrimination among materials than multispectral imaging. Nevertheless, the huge data volume that comes with single observations results in severe limitations to successful data ...
Loredana Pompilio, Monica Pepe, Giuseppe Pedrazzi, Lucia Marinangeli   +3 more
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Wavelet based segmentation of hyperspectral colon tissue imagery [PDF]

, 2003
Segmentation is an early stage for the automated classification of tissue cells between normal and malignant types. We present an algorithm for unsupervised segmentation of images of hyperspectral human colon tissue cells into their constituent parts by ...
Rajpoot, Nasir M. (Nasir Mahmood), Rajpoot, Kashif   +1 more
core   +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
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