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Strip-FFT Transformer for Single Image Deblurring

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Part of the book series:Lecture Notes in Computer Science ((LNCS,volume 14356))

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Abstract

The purpose of image deblurring is to restore the origin image from the blurred image. With the development of deep learning, better performence for image deblurring can be obtained through the deblurring methods based on CNNs, while limited ability to model the global relationship, therefore its treatment of the correlation between the original resolution pixels is relatively weak. The hot Transformer approaches have a better ability to model the global context in the early stage, howerver, the disadvantage is that it is computational complexity. In addition, using only spatial features for image deblurring may lead to poor recovery of frequency domain information from the deblurred images, and frequency domain information is also key features for image deblurring. Therefore, we propose the SFT (Strip-FFT Transformer) method, which uses a hybrid architecture of CNNs and transformers to reduce the computational complexity, and a strip-fft Attention Block that integrates attention and Res-FFT mechanism to simultaneously process spatial and frequency domain information. After experiments, it is proved that SFT can obtain state-of-the-art effect in dynamic scene deblurring with relatively low memory consumption and computational complexity.

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Acknowledgments

This study was supported by Guangdong Provincial Department of Education Characteristic Innovation Project and HanShan Normal university Doctoral Initiation Program.

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Authors and Affiliations

  1. Medical College, Shantou University, Shantou, 515041, China

    Lei Liu

  2. College of Engineering, Shantou University, Shantou, 515063, China

    Yulong Zhu, Haoyu Zhang & Weifeng Zhang

  3. College of Computer and Information Engineering, Hanshan Normal University, Chaozhou, 521041, China

    Hong Peng

Authors
  1. Lei Liu

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  2. Yulong Zhu

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  3. Haoyu Zhang

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  4. Weifeng Zhang

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  5. Hong Peng

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Corresponding author

Correspondence toHong Peng.

Editor information

Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Huchuan Lu

  2. University of Sydney, Sydney, NSW, Australia

    Wanli Ouyang

  3. Shenzhen University, Shenzhen, China

    Hui Huang

  4. Tsinghua University, Beijing, China

    Jiwen Lu

  5. Dalian University of Technology, Dalian, China

    Risheng Liu

  6. Institute of Automation, CAS, Beijing, China

    Jing Dong

  7. University of Technology Sydney, Sydney, NSW, Australia

    Min Xu

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Liu, L., Zhu, Y., Zhang, H., Zhang, W., Peng, H. (2023). Strip-FFT Transformer for Single Image Deblurring. In: Lu, H.,et al. Image and Graphics. ICIG 2023. Lecture Notes in Computer Science, vol 14356. Springer, Cham. https://doi.org/10.1007/978-3-031-46308-2_14

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