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Статті в журналах з теми "Leafspec Hyperspectral Image Calibration"
Mäkelä, Mikko, Paul Geladi, Marja Rissanen, Lauri Rautkari, and Olli Dahl. "Hyperspectral near infrared image calibration and regression." Analytica Chimica Acta 1105 (April 2020): 56–63. http://dx.doi.org/10.1016/j.aca.2020.01.019.
Повний текст джерелаZhang, Xizhen, Aiwu Zhang, Mengnan Li, Lulu Liu, and Xiaoyan Kang. "Restoration and Calibration of Tilting Hyperspectral Super-Resolution Image." Sensors 20, no. 16 (August 15, 2020): 4589. http://dx.doi.org/10.3390/s20164589.
Повний текст джерелаBurger, James, and Paul Geladi. "Hyperspectral NIR image regression part I: calibration and correction." Journal of Chemometrics 19, no. 5-7 (May 2005): 355–63. http://dx.doi.org/10.1002/cem.938.
Повний текст джерелаDavies, Matthew, Mary B. Stuart, Matthew J. Hobbs, Andrew J. S. McGonigle, and Jon R. Willmott. "Image Correction and In Situ Spectral Calibration for Low-Cost, Smartphone Hyperspectral Imaging." Remote Sensing 14, no. 5 (February 25, 2022): 1152. http://dx.doi.org/10.3390/rs14051152.
Повний текст джерелаJiang, Yonghua, Jingyin Wang, Li Zhang, Guo Zhang, Xin Li, and Jiaqi Wu. "Geometric Processing and Accuracy Verification of Zhuhai-1 Hyperspectral Satellites." Remote Sensing 11, no. 9 (April 26, 2019): 996. http://dx.doi.org/10.3390/rs11090996.
Повний текст джерелаGorretta, Nathalie, Gilles Rabatel, Jean-Michel Roger, Christophe Fiorio, Camille Lelong, and Veronique Bellon-Maurel. "Hyperspectral Imaging System Calibration Using Image Translations and Fourier Transform." Journal of Near Infrared Spectroscopy 16, no. 4 (January 2008): 371–80. http://dx.doi.org/10.1255/jnirs.809.
Повний текст джерелаAasen, H., J. Bendig, A. Bolten, S. Bennertz, M. Willkomm, and G. Bareth. "Introduction and preliminary results of a calibration for full-frame hyperspectral cameras to monitor agricultural crops with UAVs." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7 (September 19, 2014): 1–8. http://dx.doi.org/10.5194/isprsarchives-xl-7-1-2014.
Повний текст джерелаLyu, S., C. Huang, and M. Hou. "REFLECTANCE RECONSTRUCTION OF HYPERSPECTRAL IMAGE BASED ON GAUSSIAN SURFACE FITTING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 22, 2020): 1365–69. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-1365-2020.
Повний текст джерелаChang, An Jin, Jae Wan Choi, Ah Ram Song, Ye Ji Kim, and Jin Ha Jung. "Vicarious Radiometric Calibration of RapidEye Satellite Image Using CASI Hyperspectral Data." Journal of Korean Society for Geospatial Information System 23, no. 3 (September 30, 2015): 3–10. http://dx.doi.org/10.7319/kogsis.2015.23.3.003.
Повний текст джерелаKrtalić, Andrija, Vanja Miljković, Dubravko Gajski, and Ivan Racetin. "Spatial Distortion Assessments of a Low-Cost Laboratory and Field Hyperspectral Imaging System." Sensors 19, no. 19 (October 1, 2019): 4267. http://dx.doi.org/10.3390/s19194267.
Повний текст джерелаДисертації з теми "Leafspec Hyperspectral Image Calibration"
Soares, Sófacles Figueredo Carreiro. "Um novo método para transferência de modelos de calibração NIR e uma nova estratégia para classificação de sementes de algodão usando imagem hiperespectral NIR." Universidade Federal da Paraíba, 2016. http://tede.biblioteca.ufpb.br:8080/handle/tede/9237.
Повний текст джерелаMade available in DSpace on 2017-08-09T15:33:48Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 4699110 bytes, checksum: ef3b7c0aa5c4758d2c77e65ad6a81ad3 (MD5) Previous issue date: 2016-06-20
Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
This work involves the development of two studies that are presented in chapters 2 and 3. At first, a new method to perform the calibration transfer was designed. This method was developed to make use of separate variables instead of using the full spectrum or spectral windows. To accomplish this task a univariate procedure is initially used to correct the spectra recorded in the secondary equipment, given a set of transfer samples. A robust regression technique is then used to obtain a model with small sensitivity with respect to the univariate correction. The proposed method is employed in two case studies involving near infrared spectrometric determination of specific mass, research octane number and naphtenes in gasoline, and moisture and oil in corn. In both cases, better calibration transfer results were obtained in comparison with piecewise direct standardization (PDS). In the second, a new strategy for cotton seed classification using near infrared (NIR) hyperspectral images (HSI) was developed. Initially the cotton seeds samples were recorded on a station HSI image-NIR and a conventional spectrometer NIR. Thereon, the images were segmented and the mean spectrum of each seed was extract. Classification models SPA-LDA e PLS-DA based on the mean spectral were developed for two data sets. The results for models SPA-LDA and PLSDA showed that the classification with HSI-NIR data set has been achieved with greater accuracy when compared to models for the NIR-conventional data set.
Este trabalho envolve o desenvolvimento de dois estudos, que são apresentados nos capítulos 2 e 3. No primeiro, um novo método para realizar a transferência de calibração foi concebido. Este método foi desenvolvido para fazer uso de variáveis isoladas em vez de usar todo o espectro ou janelas espectrais. Para realizar essa tarefa, um procedimento univariado é inicialmente usado para corrigir os espectros registrados no equipamento secundário, dado um conjunto de amostras de transferência. Uma técnica de regressão robusta é então usada para obter um modelo com pequena sensibilidade em relação aos resíduos da correção univariada. O novo método é então empregado em dois estudos de caso envolvendo análise espectrométrica NIR, em que foram determinados os parâmetros massa específica, RON (Research Octane Number) e teor de naftênicos em gasolina e os teores de água e óleo em amostras de milho. Os resultados do novo método foram melhores do que os obtidos usando o método PDS. No segundo, uma nova estratégia para classificação de sementes de algodão usando imagens hiperespectrais no NIR foi desenvolvido. Inicialmente as amostras de sementes de algodão foram registradas em uma estação de imagem HSI-NIR e em um equipamento NIR convencional. Após isso, as imagens foram segmentadas e os espectros médios de cada semente foram extraídos. Os modelos de classificação SPA-LDA e PLS-DA baseados nos espectros médios foram construídos para os dois conjuntos de dados. Os resultados SPA-LDA e PLS-DA para os modelos demonstraram que a classificação com os dados HSI-NIR foi alcançada com maior exatidão quando comparada aos modelos obtidos usando o NIR-convencional.
Castorena-Martinez, Juan Enrique. "Non-uniformity correction and calibration of hyperspectral image data." 2010. http://hdl.handle.net/1993/21619.
Повний текст джерелаЧастини книг з теми "Leafspec Hyperspectral Image Calibration"
Lins, E. C., S. Pratavieira, W. T. Shigeyosi, M. Dutra-Correa, V. S. Bagnato, C. Kurachi, and L. G. Marcassa. "Assembly, Calibration and Application of a Hyperspectral Image System for Biomedical Imaging." In IFMBE Proceedings, 697–700. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03879-2_195.
Повний текст джерелаТези доповідей конференцій з теми "Leafspec Hyperspectral Image Calibration"
Zhang, Xia, Bing Zhang, Fangchao Hu, and Qingxi Tong. "Calibration evaluation of the spaceborne hyperspectral CHRIS image." In Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China, edited by Qingxi Tong, Wei Gao, and Huadong Guo. SPIE, 2006. http://dx.doi.org/10.1117/12.681242.
Повний текст джерелаZhang, Xia, Bing Zhang, Xiurui Geng, Qingxi Tong, and Lanfen Zheng. "Automatic flat field algorithm for hyperspectral image calibration." In Third International Symposium on Multispectral Image Processing and Pattern Recognition, edited by Hanqing Lu and Tianxu Zhang. SPIE, 2003. http://dx.doi.org/10.1117/12.539070.
Повний текст джерелаKudenov, Michael W., and Clifton G. Scarboro. "Synthetic neural network calibration of a hyperspectral imaging camera." In Image Sensing Technologies: Materials, Devices, Systems, and Applications V, edited by Nibir K. Dhar and Achyut K. Dutta. SPIE, 2018. http://dx.doi.org/10.1117/12.2305521.
Повний текст джерелаLivens, Stefan, Joris Blommaert, Dirk Nuyts, Aleksandra Sima, Pieter-Jan Baeck, and Bavo Delaure. "Radiometric calibration of the cosi hyperspectral RPAS camera." In 2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2016. http://dx.doi.org/10.1109/whispers.2016.8071688.
Повний текст джерелаCaubet, Christophe, Gilles Guerrini, Pascal Desbarats, and Jean-Philippe Domenger. "Case Study of a Calibration Problem in Acquired Hyperspectral Images." In 2022 IEEE International Conference on Image Processing (ICIP). IEEE, 2022. http://dx.doi.org/10.1109/icip46576.2022.9897839.
Повний текст джерелаBoulet, J. C., N. Gorretta, and J. M. Roger. "IDC-Improved Direct Calibration: A new direct calibration method applied to hyperspectral image analysis." In 2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2009. http://dx.doi.org/10.1109/whispers.2009.5289094.
Повний текст джерелаWang, Daming, Guorui Jia, Huijie Zhao, and Ruonan Geng. "Uncertainty analysis of in-flight spectral calibration for hyperspectral imaging spectrometers." In Image and Signal Processing for Remote Sensing, edited by Lorenzo Bruzzone, Francesca Bovolo, and Jon Atli Benediktsson. SPIE, 2017. http://dx.doi.org/10.1117/12.2277702.
Повний текст джерелаBrook, Anna, and Eyal Ben Dor. "Supervised Vicarious Calibration (SVC) of hyperspectral remote-sensing data." In 2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2011. http://dx.doi.org/10.1109/whispers.2011.6080943.
Повний текст джерелаCastro, Rodrigo, Daniel Ochoa, and Ronald Criollo. "On the influence of spectral calibration in hyperspectral image classification of leaves." In 2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON). IEEE, 2017. http://dx.doi.org/10.1109/chilecon.2017.8229687.
Повний текст джерелаMarkelin, Lauri, Eija Honkavaara, Tuure Takala, and Petri Pellikka. "Calibration and validation of hyperspectral imagery using a permanent test field." In 2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2013. http://dx.doi.org/10.1109/whispers.2013.8080708.
Повний текст джерелаЗвіти організацій з теми "Leafspec Hyperspectral Image Calibration"
Anderson, Gerald L., and Kalman Peleg. Precision Cropping by Remotely Sensed Prorotype Plots and Calibration in the Complex Domain. United States Department of Agriculture, December 2002. http://dx.doi.org/10.32747/2002.7585193.bard.
Повний текст джерела