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Oleksii S. Rubel
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- affiliation: National Aerospace University Kharkov Aviation Institute, Kharkov, Ukraine
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2020 – today
- 2022
- [c14]Viktor O. Makarichev, Galina Proskura, Oleksii S. Rubel, Vladimir V. Lukin, Benoît Vozel, Kacem Chehdi:
Lossy Compression of Three-Channel Remote Sensing Images with "Color" Component Downscaling. IGARSS 2022: 2215-2218 - [c13]Oleksii S. Rubel, Andrii S. Rubel, Vladimir V. Lukin, Karen O. Egiazarian
:
Optimal parameters selection of the Frost filter based on despeckling efficiency prediction for Sentinel SAR images. Image Processing: Algorithms and Systems 2022: 1-6 - 2021
- [j6]Oleksii S. Rubel, Vladimir V. Lukin, Sergey S. Krivenko
Reduction of Spatially Correlated Speckle in Textured SAR Images. Int. J. Comput. 20(3): 319-327 (2021) - [j5]Oleksii S. Rubel
Selection of Lee Filter Window Size Based on Despeckling Efficiency Prediction for Sentinel SAR Images. Remote. Sens. 13(10): 1887 (2021) - [c12]Andrii S. Rubel, Oleksii S. Rubel, Vladimir V. Lukin, Karen O. Egiazarian
Decision-making on image denoising expedience. Image Processing: Algorithms and Systems 2021 - [c11]Oleksii S. Rubel, Rostyslav Tsekhmystro, Vladimir V. Lukin, Karen O. Egiazarian
Benchmark of Similar Blocks Search under Noisy Conditions. Image Processing: Algorithms and Systems 2021 - 2020
- [j4]Vladimir V. Lukin, Irina V. Vasilyeva, Sergey S. Krivenko
Lossy Compression of Multichannel Remote Sensing Images with Quality Control. Remote. Sens. 12(22): 3840 (2020) - [c10]Sergey Abramov, Vladimir V. Lukin, Oleksii S. Rubel
Prediction of performance of 2D DCT-based filter and adaptive selection of its parameters. IQSP 2020 - [c9]Oleksii S. Rubel
Prediction of Lee filter performance for Sentinel-1 SAR images. IQSP 2020
2010 – 2019
- 2019
- [c8]Oleksii S. Rubel
Blind Prediction of Original Image Quality for Sentinel Sar Data. EUVIP 2019: 105-110 - [c7]Oleksii S. Rubel
Additive spatially correlated noise suppression by robust block matching and adaptive 3D filtering (JIST-first). Image Processing: Algorithms and Systems 2019 - 2018
- [j3]Oleksii S. Rubel
Is Texture Denoising Efficiency Predictable? Int. J. Pattern Recognit. Artif. Intell. 32(1): 1860005:1-1860005:32 (2018) - [c6]Oleksii S. Rubel
Blind DCT-based prediction of image denoising efficiency using neural networks. EUVIP 2018: 1-6 - 2017
- [c5]Sergey K. Abramov
Speckle reducing for Sentinel-1 SAR data. IGARSS 2017: 2353-2356 - 2016
- [j2]Aleksey Rubel
Efficiency of texture image enhancement by DCT-based filtering. Neurocomputing 175: 948-965 (2016) - [j1]Oleksii S. Rubel
Efficiency of texture image filtering and its prediction. Signal Image Video Process. 10(8): 1543-1550 (2016) - 2015
- [c4]Oleksii S. Rubel
Prediction of Despeckling Efficiency of DCT-Based Filters Applied to SAR Images. DCOSS 2015: 159-168 - [c3]Aleksey Rubel
A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise. Image Processing: Algorithms and Systems 2015: 93990P - 2014
- [c2]Aleksey Rubel
Metric performance in similar blocks search and their use in collaborative 3D filtering of grayscale images. Image Processing: Algorithms and Systems 2014: 901909 - [c1]Aleksey Rubel
Efficiency of DCT-Based Denoising Techniques Applied to Texture Images. MCPR 2014: 261-270
Coauthor Index
aka: Vladimir V. Lukin
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