Parallel feature pyramid network for image denoising

Sung Jin Cho, Kwang Hyun Uhm, Seung Wook Kim, Seo Won Ji, Sung Jea Ko

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Image denoising is a classical and essential task in consumer electronics equipped with cameras. Recently, the convolutional neural network (CNN)-based denoising methods have been widely studied. These methods adopt single-scale features to separate image structures from the noisy observation. Single-scale features, however, have limitation in covering the full characteristics of image structures at different scales. In this paper, we propose a novel denoising network that makes use of the multi-scale feature pyramid where each feature map represents the characteristics of image structure at different scales. We then combine these multi-scale features to obtain the contextual information and utilize it to effectively generate clear denoised results. Experimental results show that our network achieves superior performance to other conventional methods.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Consumer Electronics, ICCE 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728151861
DOIs
Publication statusPublished - 2020 Jan
Event2020 IEEE International Conference on Consumer Electronics, ICCE 2020 - Las Vegas, United States
Duration: 2020 Jan 42020 Jan 6

Publication series

NameDigest of Technical Papers - IEEE International Conference on Consumer Electronics
Volume2020-January
ISSN (Print)0747-668X

Conference

Conference2020 IEEE International Conference on Consumer Electronics, ICCE 2020
CountryUnited States
CityLas Vegas
Period20/1/420/1/6

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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  • Cite this

    Cho, S. J., Uhm, K. H., Kim, S. W., Ji, S. W., & Ko, S. J. (2020). Parallel feature pyramid network for image denoising. In 2020 IEEE International Conference on Consumer Electronics, ICCE 2020 [9043111] (Digest of Technical Papers - IEEE International Conference on Consumer Electronics; Vol. 2020-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE46568.2020.9043111