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Image Denoising Network Based on Subband Information Sharing Using Dual-Tree Complex Wavelet

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Abstract

The difficulty in image denoising arises from the need to recover complex texture regions. Previous methods have struggled with this task, producing images that are too smooth and are prone to aliasing and checkerboard patterns in complex regions. To address these issues, we propose an image denoising network based on subband information sharing using dual-tree complex wavelet. This network combines the spatial and transform domains through dual-tree complex wavelet transform (DTCWT) to capture both spatially structured features and time-frequency localized features for enriching the feature space. To strengthen the recovery in hard scenes, such as weak textures and high-frequency details, Subband Information Sharing Unit (SISU) is designed for the interplay of information in the transform domain, establishing the complementarity and correlation among the subbands obtained by DTCWT. Moreover, rectified linear units and exponential linear units are used in the spatial and transform domains, respectively, to match the properties of elements in different domains. Comprehensive experiments demonstrate the powerful recovery capability of the network for both textured and smooth regions, as well as the competitive results of the network in non-blind/blind image denoising.

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Notes

  1. The code is available at https://github.com/gyp67/Denoising_SISU_DTCWT.

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Acknowledgements

This work is supported by the Major Special Science and Technology Project of Anhui Province (No. 201903a06020006) and the Key Project of Education Natural Science Research of Anhui Province of China (No. KJ2017A353).

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Authors and Affiliations

  1. School of Computer and Information, Anqing Normal University, Anqing, 246133, Anhui, China

    Kui Liu & Yiping Guo

  2. Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing, 246133, Anhui, China

    Kui Liu, Yiping Guo & Benyue Su

  3. School of Mathematics and Computer, Tongling University, Tongling, 244061, Anhui, China

    Benyue Su

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Liu, K., Guo, Y. & Su, B. Image Denoising Network Based on Subband Information Sharing Using Dual-Tree Complex Wavelet. Neural Process Lett 55, 10975–10991 (2023). https://doi.org/10.1007/s11063-023-11359-1

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