Oleksii Rubel
Oleksii Rubel
Associate Professor, National Aerospace University "KhAI", Kharkiv, Ukraine
Verified email at - Homepage
Cited by
Cited by
An improved prediction of DCT-based image filters efficiency using regression analysis
OS Rubel, VV Lukin
Information and Telecommunication Sciences, 30-41, 2014
Efficiency of DCT-based denoising techniques applied to texture images
A Rubel, V Lukin, O Pogrebnyak
Pattern Recognition: 6th Mexican Conference, MCPR 2014, Cancun, Mexico, June …, 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
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
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
Selection of lee filter window size based on despeckling efficiency prediction for sentinel sar images
O Rubel, V Lukin, A Rubel, K Egiazarian
Remote Sensing 13 (10), 1887, 2021
Lossy compression of multichannel remote sensing images with quality control
V Lukin, I Vasilyeva, S Krivenko, F Li, S Abramov, O Rubel, B Vozel, ...
Remote Sensing 12 (22), 3840, 2020
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
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
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
NN-based prediction of sentinel-1 SAR image filtering efficiency
O Rubel, V Lukin, A Rubel, K Egiazarian
Geosciences 9 (7), 290, 2019
Additive spatially correlated noise suppression by robust block matching and adaptive 3D filtering (JIST-first)
O Rubel, V Lukin, K Egiazarian
Electronic Imaging 31, 1-11, 2018
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
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
Analysis of visual quality for denoised images
A Rubel, O Rubel, V Lukin
2017 14th International Conference The Experience of Designing and …, 2017
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, 1543-1550, 2016
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
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, 184-195, 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, 65-76, 2014
Block matching and 3D collaborative filtering adapted to additive spatially correlated noise
A Rubel, V Lukin, K Egiazarian
Proceedings of 9th International Workshop on Video Processing and Quality …, 2015
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