Image database TID2013: Peculiarities, results and perspectives N Ponomarenko, L Jin, O Ieremeiev, V Lukin, K Egiazarian, J Astola, ... Signal processing: Image communication 30, 57-77, 2015 | 1347 | 2015 |
Color image database TID2013: Peculiarities and preliminary results N Ponomarenko, O Ieremeiev, V Lukin, K Egiazarian, L Jin, J Astola, ... European workshop on visual information processing (EUVIP), 106-111, 2013 | 634 | 2013 |
Multicomponent image segmentation using a genetic algorithm and artificial neural network M Awad, K Chehdi, A Nasri IEEE Geoscience and remote sensing letters 4 (4), 571-575, 2007 | 130 | 2007 |
Local signal-dependent noise variance estimation from hyperspectral textural images ML Uss, B Vozel, VV Lukin, K Chehdi IEEE Journal of Selected Topics in Signal Processing 5 (3), 469-486, 2011 | 125 | 2011 |
Unsupervised clustering method with optimal estimation of the number of clusters: Application to image segmentation C Rosenberger, K Chehdi Proceedings 15th International Conference on Pattern Recognition. ICPR-2000 …, 2000 | 112 | 2000 |
A new color image database TID2013: Innovations and results N Ponomarenko, O Ieremeiev, V Lukin, L Jin, K Egiazarian, J Astola, ... Advanced Concepts for Intelligent Vision Systems: 15th International …, 2013 | 103 | 2013 |
BandClust: An unsupervised band reduction method for hyperspectral remote sensing C Cariou, K Chehdi, S Le Moan IEEE Geoscience and Remote Sensing Letters 8 (3), 565-569, 2010 | 101 | 2010 |
Regional prediction of soil organic carbon content over temperate croplands using visible near-infrared airborne hyperspectral imagery and synchronous field spectra E Vaudour, JM Gilliot, L Bel, J Lefevre, K Chehdi International Journal of applied earth observation and geoinformation 49, 24-38, 2016 | 97 | 2016 |
Genetic fusion: application to multi-components image segmentation C Rosenberger, K Chehdi 2000 IEEE International Conference on Acoustics, Speech, and Signal …, 2000 | 84 | 2000 |
Unsupervised nearest neighbors clustering with application to hyperspectral images C Cariou, K Chehdi IEEE Journal of Selected Topics in Signal Processing 9 (6), 1105-1116, 2015 | 78 | 2015 |
Image informative maps for component-wise estimating parameters of signal-dependent noise ML Uss, B Vozel, VV Lukin, K Chehdi Journal of Electronic Imaging 22 (1), 013019-013019, 2013 | 74 | 2013 |
Lossy compression of hyperspectral images based on noise parameters estimation and variance stabilizing transform AN Zemliachenko, RA Kozhemiakin, ML Uss, SK Abramov, ... Journal of applied remote sensing 8 (1), 083571-083571, 2014 | 68 | 2014 |
Automatic image segmentation system through iterative edge–region co-operation CD Kermad, K Chehdi Image and Vision Computing 20 (8), 541-555, 2002 | 68 | 2002 |
Identification of the nature of noise and estimation of its statistical parameters by analysis of local histograms L Beaurepaire, K Chehdi, B Vozel 1997 IEEE International Conference on Acoustics, Speech, and Signal …, 1997 | 65 | 1997 |
Methods and automatic procedures for processing images based on blind evaluation of noise type and characteristics VV Lukin, SK Abramov, NN Ponomarenko, ML Uss, M Zriakhov, B Vozel, ... Journal of applied remote sensing 5 (1), 053502-053502-26, 2011 | 59 | 2011 |
A new k-nearest neighbor density-based clustering method and its application to hyperspectral images C Cariou, K Chehdi 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2016 | 58 | 2016 |
Image informative maps for estimating noise standard deviation and texture parameters M Uss, B Vozel, V Lukin, S Abramov, I Baryshev, K Chehdi EURASIP journal on advances in signal processing 2011, 1-12, 2011 | 56 | 2011 |
Maximum likelihood estimation of spatially correlated signal-dependent noise in hyperspectral images ML Uss, B Vozel, VV Lukin, K Chehdi Optical Engineering 51 (11), 111712-111712, 2012 | 51 | 2012 |
Multi-component image segmentation using a hybrid dynamic genetic algorithm and fuzzy C-means M Awad, K Chehdi, A Nasri IET image processing 3 (2), 52-62, 2009 | 50 | 2009 |
Lossy compression of noisy remote sensing images with prediction of optimal operation point existence and parameters AN Zemliachenko, SK Abramov, VV Lukin, B Vozel, K Chehdi Journal of Applied Remote Sensing 9 (1), 095066-095066, 2015 | 45 | 2015 |