J. H. Wang, C. J. Zhao, and W. Huang, Basis and Application of Quantitative Remote Sensing in Agriculture, pp.141-184, 2008.

D. C. Singh, J. Jayas, N. D. Paliwal, and . White, Detection of insect-damaged wheat kernels using near-infrared hyperspectral imaging, Journal of Stored Products Research, vol.45, issue.3, pp.151-158, 2009.
DOI : 10.1016/j.jspr.2008.12.002

M. N. Nguyen-do-trong, B. M. Tsuta, J. Nicola, W. De-baerdemaeker, and . Saeys, Prediction of optimal cooking time for boiled potatoes by hyperspectral imaging, Journal of Food Engineering, vol.105, issue.4, pp.617-624, 2011.
DOI : 10.1016/j.jfoodeng.2011.03.031

M. L. Liu, S. O. Ngadi, C. Prasher, and . Garié-py, Categorization of pork quality using Gabor filter-based hyperspectral imaging technology, Journal of Food Engineering, vol.99, issue.3, pp.284-293, 2010.
DOI : 10.1016/j.jfoodeng.2010.03.001

M. Rozni and M. Yusof, Trends and Issues in Noise Reduction for Hyperspectral Vegetation Reflectance Spectra, European Journal of Scientific Research, vol.29, issue.3, pp.404-410, 2009.

W. Ying and M. Jinyuan, A New De-Noising Technique for Spectra Based on Mexican Hat Wavelet, Spectroscopy and Spectral Analysis, vol.25, issue.1, pp.124-127, 2005.

W. Zhou-dan, T. Qinjun, L. Qingjiu, F. Qizhong, and . Wenxue, Wavelet Analysis and Its Application in Denoising the Spectrum of Hyperspectral Image, Spectroscopy and Spectral Analysis, issue.7, pp.29-1941, 2009.

B. Hu, Q. Li, and A. Smith, Noise reduction of hyperspectral data using singular spectral analysis, International Journal of Remote Sensing, vol.36, issue.9, pp.30-1954, 2009.
DOI : 10.1016/0167-2789(92)90103-T

L. Jin, W. Wan, Y. Wu, B. Cui, and X. Yu, A General Framework for High-Dimensional Data Reduction Using Unsupervised Bayesian Model, Communications in Computer and Information Science, vol.57, issue.4, pp.98-96, 2010.
DOI : 10.1109/TC.2007.70811

S. Lei, G. De-feng, and L. Jian-shu, Hyperspectral Imagery Denoising Method Based on Wavelets, Spectroscopy and Spectral Analysis, issue.7, pp.29-1954, 2009.

G. Chen and S. Qian, Simultaneous dimensionality reduction and denoising of hyperspectral imagery using bivariate wavelet shrinking and principal component analysis, Canadian Journal of Remote Sensing, vol.3753, issue.6, pp.34-447, 2008.
DOI : 10.5589/m08-058

L. L. Gómez-chova, L. Alonso, G. Guanter, J. Camps-valls, J. Calpe et al., Correction of systematic spatial noise in push-broom hyperspectral sensors: application to CHRIS/PROBA images, Applied Optics, vol.47, issue.28, pp.47-93, 2008.
DOI : 10.1364/AO.47.000F46

M. Nguyen-quang, Image smoothing of multispectral imagery based on the HNN and geo-statistics, Journal of Remote Sensing, vol.15, issue.3, pp.640-644, 2011.

K. S. Schmidt and A. K. Skidmore, Smoothing vegetation spectra with wavelets, International Journal of Remote Sensing, vol.25, issue.6, pp.25-1167, 2004.
DOI : 10.1016/S0034-4257(98)00032-7

I. Atkinson, F. Kamalabadi, and D. L. Jones, Wavelet-based hyperspectral image estimation, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), pp.743-745, 2003.
DOI : 10.1109/IGARSS.2003.1293903

T. Jolliffe, Principal component analysis, 2002.
DOI : 10.1007/978-1-4757-1904-8

C. Weiwei, G. Lei, L. Kun, and F. Chaoyang, A noise removal method for hyperspectral data based on Contourlet transformation and PCA analysis, Journal of Electronics & Information Technology, issue.12, pp.31-2892, 2009.

K. Fukunaga, Introduction to statistical pattern recognition, 1990.

H. Othman and S. Qian, Noise reduction of hyperspectral imagery using hybrid spatial-spectral derivative-domain wavelet shrinkage, IEEE Transactions on Geoscience and Remote Sensing, vol.44, issue.2, pp.397-408, 2006.
DOI : 10.1109/TGRS.2005.860982

H. Mingxiang, W. Ke, S. Zhou, G. Jianhua, L. Hongyi et al., Quantitative Evaluation of Soil Hyperspectra Denoising with Different Filters, Spectroscopy and Spectral Analysis, issue.3, pp.29-722, 2009.