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
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
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
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
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
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
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
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
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
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
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
Block matching and 3D collaborative filtering adapted to additive spatially correlated noise
A Rubel, V Lukin, K Egiazarian
Proceedings of VPQM, 6, 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
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
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
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
NN-based prediction of sentinel-1 SAR image filtering efficiency
O Rubel, V Lukin, A Rubel, K Egiazarian
Geosciences 9 (7), 290, 2019
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