Multi-image deblurring using complement

Pei Wang, Jinqiu Sun, Haisen Li, Xueling Chen, Yu Zhu, Yanning Zhang

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

Abstract

The purpose of image restoration is to recover the latent image from the observed blurred images. In multi-image restoration, the input image’s quality directly affects the final deblurring result. In this paper, a blurry images restoration method based on the complement is proposed for the selection of images in multi-image restoration. First, we give a description of complement between different images. Then, the blurred images of maximum complement are selected by image selection method which is based on the iterative maximum complement. Finally, we use an existing deblurring method to estimate the latent image. We compare the new method with traditional methods, the experimental results clearly demonstrate the efficacy of the proposed method.

Original languageEnglish
Title of host publicationIntelligence Science and Big Data Engineering - 7th International Conference, IScIDE 2017, Proceedings
EditorsYi Sun, Huchuan Lu, Lihe Zhang, Jian Yang, Hua Huang
PublisherSpringer Verlag
Pages549-558
Number of pages10
ISBN (Print)9783319677767
DOIs
StatePublished - 2017
Event7th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2017 - Dalian, China
Duration: 22 Sep 201723 Sep 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10559 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2017
Country/TerritoryChina
CityDalian
Period22/09/1723/09/17

Keywords

  • Complement
  • Image deblurring
  • Multi-image deblurring

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