| An improved prediction of DCT-based image filters efficiency using regression analysis OS Rubel, VV Lukin National Technical University of Ukraine “Kyiv Polytechnic Institute”, 2014 | 35 | 2014 |
| Efficiency of DCT-based denoising techniques applied to texture images A Rubel, V Lukin, O Pogrebnyak Mexican Conference on Pattern Recognition, 261-270, 2014 | 28 | 2014 |
| Efficiency of texture image enhancement by DCT-based filtering A Rubel, V Lukin, M Uss, B Vozel, O Pogrebnyak, K Egiazarian Neurocomputing 175, 948-965, 2016 | 25 | 2016 |
| Impact of SAR data filtering on crop classification accuracy M Lavreniuk, N Kussul, M Meretsky, V Lukin, S Abramov, O Rubel 2017 IEEE First Ukraine Conference on Electrical and Computer Engineering …, 2017 | 23 | 2017 |
| Is Texture Denoising Efficiency Predictable? O Rubel, V Lukin, S Abramov, B Vozel, O Pogrebnyak, K Egiazarian International Journal of Pattern Recognition and Artificial Intelligence 32 …, 2018 | 22 | 2018 |
| Prediction of Despeckling Efficiency of DCT-based filters Applied to SAR Images OS Rubel, VV Lukin, FS de Medeiros 2015 International Conference on Distributed Computing in Sensor Systems …, 2015 | 16 | 2015 |
| Efficiency of texture image filtering and its prediction O Rubel, V Lukin, S Abramov, B Vozel, K Egiazarian, O Pogrebnyak Signal, Image and Video Processing 10 (8), 1543-1550, 2016 | 13 | 2016 |
| HVS-based local analysis of denoising efficiency for DCT-based filters O Rubel, N Ponomarenko, V Lukin, J Astola, K Egiazarian 2015 Second International Scientific-Practical Conference Problems of …, 2015 | 13 | 2015 |
| DCT-Based Color Image Denoising: Efficiency Analysis and Prediction V Lukin, S Abramov, R Kozhemiakin, A Rubel, M Uss, N Ponomarenko, ... Color Image and Video Enhancement, 55-80, 2015 | 12 | 2015 |
| Despeckling of multitemporal sentinel SAR images and its impact on agricultural area classification V Lukin, O Rubel, R Kozhemiakin, S Abramov, A Shelestov, M Lavreniuk, ... Recent Advances and Applications in Remote Sensing, 21-40, 2018 | 10 | 2018 |
| Analysis of visual quality for denoised images A Rubel, O Rubel, V Lukin 2017 14th International Conference The Experience of Designing and …, 2017 | 10 | 2017 |
| A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise AS Rubel, VV Lukin, KO Egiazarian Image Processing: Algorithms and Systems XIII 9399, 93990P, 2015 | 9 | 2015 |
| Blind DCT-based prediction of image denoising efficiency using neural networks O Rubel, A Rubel, V Lukin, K Egiazarian 2018 7th European Workshop on Visual Information Processing (EUVIP), 1-6, 2018 | 8 | 2018 |
| Performance prediction for 3D filtering of multichannel images O Rubel, RA Kozhemiakin, SK Abramov, VV Lukin, B Vozel, K Chehdi Image and Signal Processing for Remote Sensing XXI 9643, 96430D, 2015 | 8 | 2015 |
| Block matching and 3D collaborative filtering adapted to additive spatially correlated noise A Rubel, V Lukin, K Egiazarian Proceedings of VPQM, 6, 2015 | 8 | 2015 |
| Speckle reducing for Sentinel-1 SAR data S Abramov, O Rubel, V Lukin, R Kozhemiakin, N Kussul, A Shelestov, ... 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2017 | 7 | 2017 |
| A method for predicting denoising efficiency for color images OS Rubel, RO Kozhemiakin, SS Krivenko, VV Lukin, B Vozel, K Chehdi 2015 IEEE 35th International Conference on Electronics and Nanotechnology …, 2015 | 7 | 2015 |
| A neural network based predictor of filtering efficiency for image enhancement A Rubel, A Naumenko, V Lukin 2014 IEEE Microwaves, Radar and Remote Sensing Symposium (MRRS), 14-17, 2014 | 7 | 2014 |
| Metric performance in similar blocks search and their use in collaborative 3D filtering of grayscale images AS Rubel, VV Lukin, KO Egiazarian Image Processing: Algorithms and Systems XII 9019, 901909, 2014 | 7 | 2014 |
| NN-based prediction of sentinel-1 SAR image filtering efficiency O Rubel, V Lukin, A Rubel, K Egiazarian Geosciences 9 (7), 290, 2019 | 6 | 2019 |
Vladimir Lukin, Âëàäèìèð ËóêèíNational Aerospace University, Kharkov, UkraineVerified email at ai.kharkov.com
