Results 91 to 100 of about 45,417 (317)

Evaluating the Effect of Different Wheat Rust Disease Symptoms on Vegetation Indices Using Hyperspectral Measurements

Remote Sensing, 2014
Spectral Vegetation Indices (SVIs) have been widely used to indirectly detect plant diseases. The aim of this research is to evaluate the effect of different disease symptoms on SVIs and introduce suitable SVIs to detect rust disease.
Davoud Ashourloo, Mohammad Reza Mobasheri, Alfredo Huete   +2 more
doaj   +1 more source

Toward Intelligent Multimodal Holography for Real‐Time Chemical Imaging of Dynamic Ion Separation

Advanced Intelligent Discovery, EarlyView.
Intelligent multimodal holography integrates digital off‐axis holography, spectroscopic imaging, and AI‐driven reconstruction to visualize ion transport and chemical dynamics in real time. In this perspective paper, we outline how this approach enables label‐free, chemically specific monitoring of complex environments and discuss its potential to ...
Giovanna Ricchiuti, Sarah I. Allec, Maxim Ziatdinov, Venkateshkumar Prabhakaran   +3 more
wiley   +1 more source

Nonlinear unmixing of minerals based on the log and continuum removal model

European Journal of Remote Sensing, 2019
Spectral mixing models for minerals can be complex, and choosing the right unmixing model is indispensable to ensure the accuracy of spectral unmixing. Continuum removal (CR) and natural log operation have the potential to eliminate nonlinear effects in ...
Hengqian Zhao, Xuesheng Zhao
doaj   +1 more source

Supervised Distance-Based Feature Selection for Hyperspectral Target Detection

Remote Sensing, 2019
Feature/band selection (FS/BS) for target detection (TD) attempts to select features/bands that increase the discrimination between the target and the image background. Moreover, TD usually suffers from background interference. Therefore, bands that help
Amir Moeini Rad, Ali Akbar Abkar, Barat Mojaradi   +2 more
doaj   +1 more source

EnMAP - The future hyperspectral Satellite Mission Product Generation

, 2009
The basic components of the future German satellite mission EnMAP (Environmental Mapping and Analysis Program) are the project management led by the Space Agency of the German Aerospace Centre (DLR) located in Bonn-Oberkassel, the space segment ...
Neumann, Andreas, Storch, Tobias, Miguel, Amaia, Kaufmann, hermann, Bachmann, Martin, Müller, Andreas, Palubinskas, Gintautas, Schneider, Mathias, Makasy, Christine, Richter, Rudolf, Guanter, Luis, Müller, Rupert, Walzel, Thomas, Segl, Karl   +13 more
core  

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

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Thermal remote sensing from Airborne Hyperspectral Scanner data in the framework of the SPARC and SEN2FLEX projects: an overview [PDF]

, 2009
The AHS (Airborne Hyperspectral Scanner) instrument has 80 spectral bands covering the visible and near infrared (VNIR), short wave infrared (SWIR), mid infrared (MIR) and thermal infrared (TIR) spectral range.
Gillespie, A., L. Guanter, Sobrino, JA, M. Romaguera, Z. Su, J. C. Jiménez-Muñoz, Guanter, L, Nerry, Françoise, F. Nerry, Jia, L, Morales, L., Olioso, A, Jiménez-Miñoz, J. C., Guanter, Luis, L. Morales, Mattar, Cristian, V. Hidalgo, Morales, L.M., Romaguera Albentosa, M., Jia, L., Sobrino, J.A., Cuenca, J, Zarco-Tejada, P.J., J. A. Sobrino, Olioso, A., Su, Zhongbo, E. de Miguel, Sobrino, J. A., W. Timmermans, Su, Z., Y. Julien, J. Cuenca, Gillespie, A, L. Balick, Julien, Y, Soria, G., Moreno, José, Balick, L, A. Gieske, Franch, B, C. Mattar, de Miguel, E, Romaguera, M, Sepulcre-Canto, G., Moreno, J., Shen, Q., J. Moreno, Julien, Y., Hidalgo, V., D. Sabol, Timmermans, W., Franch, B., Soria, G, Sabol, D, Zarco-Tejada, P. J., Timmermans, W, Gieske, A.S.M., Q. Shen, A. Gillespie, Shen, Q, Miguel, E., de, Nerry, F., Su, Z, Gillespie, A.R., Romaguera, M., Mattar, C., ... [et al.], Gieske, A., Nerry, F, Balick, L., Guanter, L., Timmermans, W.J., L. Jia, Olioso, Albert, P. J. Zarco-Tejada, Cuenca, J., G. Sepulcre-Cantó, Jimenez-Munoz, J.C., Sepulcre-Canto, G, Su, Z.; id_orcid, Gieske, A, Moreno, J, de Miguel, E., Hidalgo, V, Sabol, D., Morales, L, Soria, E., B. Franch, Jimenez-Munoz, JC, G. Sòria, A. Olioso, Mattar, C, Zarco-Tejada, PJ   +92 more
core   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

Models and Methods for Automated Background Density Estimation in Hyperspectral Anomaly Detection

, 2012
Detecting targets with unknown spectral signatures in hyperspectral imagery has been proven to be a topic of great interest in several applications. Because no knowledge about the targets of interest is assumed, this task is performed by searching the ...
VERACINI, TIZIANA
core