WGAN based edge preserved de-blurring using perceptual style similarity

Minsoo Hong, Yoonsik Choe

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

Abstract

Generative Adversarial Network (GAN) is an effective generative model and can be used for de-blurring. In this paper, we propose an edge preserved de-blurring method using Wasserstein generative adversarial network with gradient penalty (WGAN-GP), which is based on conditional GAN. Also, since detailed-edge is the most important factor in de-blurred image, in order to preserve detailed-edge and capture its perceptual similarity, the style loss function is added to represent the perceptual information of the edge. Consequently, the proposed method improves the similarity between sharp images and blurred images by minimizing Wasserstein distance, and well captures the perceptual similarity using style loss function, considering the correlation of features in Convolutional Neural Network. Experiments depict that the proposed method achieves 0.98 in SSIM that is higher performance, compared to other conventional methods such as filter based methods and content based method.

Original languageEnglish
Title of host publicationProceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages58-61
Number of pages4
ISBN (Electronic)9781538670361
DOIs
Publication statusPublished - 2019 Feb 19
Event4th International Symposium on Computer, Consumer and Control, IS3C 2018 - Taichung, Taiwan, Province of China
Duration: 2018 Dec 62018 Dec 8

Publication series

NameProceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018

Conference

Conference4th International Symposium on Computer, Consumer and Control, IS3C 2018
CountryTaiwan, Province of China
CityTaichung
Period18/12/618/12/8

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Control and Systems Engineering
  • Energy Engineering and Power Technology
  • Computer Science Applications
  • Control and Optimization
  • Signal Processing

Fingerprint Dive into the research topics of 'WGAN based edge preserved de-blurring using perceptual style similarity'. Together they form a unique fingerprint.

  • Cite this

    Hong, M., & Choe, Y. (2019). WGAN based edge preserved de-blurring using perceptual style similarity. In Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018 (pp. 58-61). [8644758] (Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IS3C.2018.00023