Oleksii Rubel
Oleksii Rubel
National Aerospace University "KhAI", Kharkiv, Ukraine
Подтвержден адрес электронной почты в домене khai.edu - Главная страница
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
Efficiency of DCT-based denoising techniques applied to texture images
A Rubel, V Lukin, O Pogrebnyak
Mexican Conference on Pattern Recognition, 261-270, 2014
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
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
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
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
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
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
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
Analysis of visual quality for denoised images
A Rubel, O Rubel, V Lukin
2017 14th International Conference The Experience of Designing and …, 2017
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
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
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
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
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
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
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
Block matching and 3D collaborative filtering adapted to additive spatially correlated noise
A Rubel, V Lukin, K Egiazarian
Proceedings of VPQM, 6, 2015
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
An approach to prediction of signal-dependent noise removal efficiency by DCT-based filter
VV Lukin, SK Abramov, A Rubel, SS Krivenko, A Naumenko, B Vozel, ...
Telecommunications and Radio Engineering 73 (18), 2014
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