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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/41659
Title: Image enhancement by 2D non-separable quaternionic filter bank-based thresholding neural network
Authors: Avramov, V. V.
Rybenkov, E. V.
Petrovsky, N. A.
Keywords: публикации ученых;image enhancement;thresholding neural network
Issue Date: 2019
Publisher: Springer
Citation: Avramov, V. V. Image enhancement by 2D non-separable quaternionic filter bank-based thresholding neural network / 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. 207–212.
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 =17,15 dB, prototype filter bank (8x24) 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 1 1.5 dB higher.
URI: https://libeldoc.bsuir.by/handle/123456789/41659
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