https://libeldoc.bsuir.by/handle/123456789/41685| Title: | Thresholding Neural Network Image Enhancement Based on 2-D Non-separable Quaternionic Filter Bank |
| Authors: | Avramov, V. V. Rybenkov, E. V. Petrovsky, N. A. |
| Keywords: | авторефераты диссертаций;image enhancement;thresholding neural network |
| Issue Date: | 2019 |
| Publisher: | Springer |
| Citation: | Avramov, V. V. Thresholding Neural Network Image Enhancement Based on 2-D Non-separable Quaternionic Filter Bank / V. V. Avramov, E. V. Rybenkov, N. A. Petrovsky // Pattern Recognition and Information Processing : 14th International conference, Minsk, 21–23 may 2019 / Springer. – Minsk, 2019. – P. 147–161. – DOI: https://doi.org/10.1007/978-3-030-35430-5_13. |
| Abstract: | The thresholding neural network with a 2-D non-separable paraunitary filter bank based on quaternion multipliers (2-D NSQ-PUFB) for image enhancement is proposed. Due to the high characteristics of the multi-bands 2-D NSQ-PUFB (structure “64in-64out”, CG2D=17,15dB , prototype filter bank ( 8×24 ) Q-PUFB), which forms the basis of the TNN, the results of noise editing in comparison with the approaches based on the two-channel wavelet transform in terms of PSNR are 1dB – 1.5dB higher. |
| URI: | https://libeldoc.bsuir.by/handle/123456789/41685 |
| Appears in Collections: | Публикации в зарубежных изданиях |
| File | Description | Size | Format | |
|---|---|---|---|---|
| Avramov_Thresholding.pdf | 21.91 kB | Adobe PDF | View/Open |
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