Results 71 to 80 of about 345,137 (201)

Nonlinearity detection in hyperspectral images using a polynomial post-nonlinear mixing model [PDF]

, 2012
This paper studies a nonlinear mixing model for hyperspectral image unmixing and nonlinearity detection. The proposed model assumes that the pixel reflectances are nonlinear functions of pure spectral components contaminated by an additive white Gaussian
Altmann, Yoann, Altmann, Yoann; id_orcid, Dobigeon, Nicolas, Tourneret, Jean-Yves   +3 more
core   +1 more source

Mapping urban impervious surfaces from an airborne hyperspectral imagery using the object-oriented classification approach

MATEC Web of Conferences, 2017
The objective of this research is to explore the capabilities of the hyperspectral imagery in mapping the urban impervious objects and identifying the surface materials using an object-oriented approach.
Aguejdad Rahim, Serradj Aziz, Weber Christiane   +2 more
doaj   +1 more source

A COMPARISON OF LIDAR REFLECTANCE AND RADIOMETRICALLY CALIBRATED HYPERSPECTRAL IMAGERY [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
In order to retrieve results comparable under different flight parameters and among different flight campaigns, passive remote sensing data such as hyperspectral imagery need to undergo a radiometric calibration.
A. Roncat, C. Briese, C. Briese, N. Pfeifer   +3 more
doaj   +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
core   +1 more source

Hyperspectral Image Resolution Enhancement Based on Spectral Unmixing and Information Fusion [PDF]

, 2011
Hyperspectral imaging sensors exibit high spectral resolution, but normally low spatial resolution. This leads to spectral signatures of pixels originating from different object types. Such pixels are called mixed pixels.
Avbelj, Janja, Reinartz, Peter, Müller, Rupert, Cerra, Daniele, Bieniarz, Jakub   +4 more
core  

Hyperspectral image unmixing using a multiresolution sticky HDP [PDF]

, 2012
This paper is concerned with joint Bayesian endmember extraction and linear unmixing of hyperspectral images using a spatial prior on the abundance vectors.We propose a generative model for hyperspectral images in which the abundances are sampled from a ...
Hero, Alfred O., Dobigeon, Nicolas, Hero, Alfred, Mittelman, Roni   +3 more
core   +1 more source

Development of a new spectral library classifier for airborne hyperspectral images on heterogeneous environments [PDF]

, 2011
The classification of hyperspectral images on heterogeneous environments without prior knowledge about the study area is a challenging task. Finding potential pure spectral signatures or endmembers (EM) of the various surface materials within an image is
Mende, Andre, Heiden, Uta, Buchroithner, Manfred, Hoja, Danielle, Bachmann, Martin   +4 more
core  

Illumination invariance and shadow compensation via spectro-polarimetry technique [PDF]

, 2013
A major problem for obtaining target reflectance via hyperspectral imaging systems is the presence of illumination and shadow effects. These factors are common artefacts, especially when dealing with a hyperspectral imaging system that has sensors in the
Jackman, James, Soori, Umair, Hong, Kan, Ibrahim, Izzati, Richardson, Mark A., Yuen, Peter W. T., Chen, Tong   +6 more
core   +1 more source

Machine Learning-Based Detection and Quantification of Septoria Leaf Blotch in Winter Wheat from Hyperspectral and UAV Multispectral Data

Remote Sensing
Septoria leaf blotch (SLB), caused by Zymoseptoria tritici, is one of the most destructive foliar diseases of wheat and requires accurate methods for early detection and disease severity assessment. This study evaluated the potential of hyperspectral ASD
Andrzej Wójtowicz, Jan Piekarczyk, Marek Wójtowicz, Sławomir Królewicz, Ilona Świerczyńska, Katarzyna Pieczul, Magdalena Jakubowska, Jakub Ceglarek   +7 more
doaj   +1 more source

Estimating the number of endmembers in hyperspectral images using the normal compositional model and a hierarchical Bayesian algorithm. [PDF]

, 2010
This paper studies a semi-supervised Bayesian unmixing algorithm for hyperspectral images. This algorithm is based on the normal compositional model recently introduced by Eismann and Stein.
Eches, Olivier, Dobigeon, Nicolas, Tourneret, Jean-Yves   +2 more
core   +1 more source