Image Enhancement Using Deblur Generative Network and Deep Deblur Adversarial

Purbandini, Chastine Fatichah, Bilqis Amaliah

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The increased use of digital cameras has given rise to new challenges such as reduced image quality resulting in poor clarity or distortion, which can result in loss or unclearness of recorded information. To overcome this problem, deep learning-based approaches such as DeblurGAN and DeepDeblur have been developed for the clarity of blurry images. This research aims to compare the performance of the two approaches in the context of improving the clarity of blurry images. The research steps include collecting data from the GoPro dataset, dividing the data into training data and test data, analyzing the data using the DeblurGAN and DeepDeblur methods, and evaluating the results using Structural Similarity Index Measure (SSIM), Mean Square Estimation (MSE), and Peak Signal-to-Noise Ratio (PSNR). The evaluation results show that the DeblurGAN method achieves the best results with SSIM values of 0.958, MSE of 0.00057, and PSNR of 33.18. This shows that DeblurGAN has better evaluation performance compared to Deep Deblur in improving the clarity of blurry images.

Original languageEnglish
Title of host publicationProceedings of the 2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages136-141
Number of pages6
ISBN (Electronic)9798350353464
DOIs
Publication statusPublished - 2024
Event2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024 - Hybrid, Bali, Indonesia
Duration: 4 Jul 20246 Jul 2024

Publication series

NameProceedings of the 2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024

Conference

Conference2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024
Country/TerritoryIndonesia
CityHybrid, Bali
Period4/07/246/07/24

Keywords

  • blur image
  • DeblurGAN
  • DeepDeblur
  • image enhancement
  • motion blur image

Fingerprint

Dive into the research topics of 'Image Enhancement Using Deblur Generative Network and Deep Deblur Adversarial'. Together they form a unique fingerprint.

Cite this