Inverted Residual Fourier Transformation for Lightweight Single Image Deblurring

Shunsuke Yae, Masaaki Ikehara

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

In recent years, encoder-decoder structures are widely used for single image deblurring and successfully restore high quality images. How-ever, FLOPs and the number of parameters tend to increase to restore a high-quality image. Thus, we propose a new lightweight network (IRFTNet) based on DeepRFT. This network has two features to improve performance and lightweight. First, a new backbone called Inverted Residual Fourier Transformation block (IRFTblock) based on inverted residual block is introduced to decrease computational complexity. Second, a new module called Lower Feature Synthesis (LFS) was introduced to efficiently transfer encoder information from lower layers to upper layers. These improvements resulted in a 32.98dB in PSNR on the GoPro dataset, despite approximately half FLOPs and the number of parameters of DeepRFT.

本文言語English
ホスト出版物のタイトル2023 IEEE International Conference on Consumer Electronics, ICCE 2023
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781665491303
DOI
出版ステータスPublished - 2023
イベント2023 IEEE International Conference on Consumer Electronics, ICCE 2023 - Las Vegas, United States
継続期間: 2023 1月 62023 1月 8

出版物シリーズ

名前Digest of Technical Papers - IEEE International Conference on Consumer Electronics
2023-January
ISSN(印刷版)0747-668X

Conference

Conference2023 IEEE International Conference on Consumer Electronics, ICCE 2023
国/地域United States
CityLas Vegas
Period23/1/623/1/8

ASJC Scopus subject areas

  • 産業および生産工学
  • 電子工学および電気工学

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