Coupled convolution method for image processing

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

Abstract

This paper develops a Coupled Convolution Model (CCM) for Error Concealment (EC), Image Super Resolution (ISR) and Multifocus Image Fusion (MIF) used in unmanned aerial vehicles. The key points of this paper are: I) for EC, to efficiently exploit the inherent correlation relationship between the lost region and its known adjacent region, this paper introduces a special CCM in order that their convolution model results via different convolution filters are close to the counterpart on the convolution space; ii) for ISR, we develop CCM to train two convolution filters and map the original low-resolution(LR) and high-resolution(HR) image patches onto a unified convolution subspace. iii) as for MIF, since image fusion depends on the local information of source images resulting from the same scene, this paper constructs a special Coupled Two-Dimensional Convolution Model (2D-CCM) for the image patches from different source images. Experimental results show that the proposed CCM is very effective for EC, ISR and MIF.

Original languageEnglish
Title of host publicationProceedings of 2017 IEEE International Conference on Unmanned Systems, ICUS 2017
EditorsXin Xu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages512-516
Number of pages5
ISBN (Electronic)9781538631065
DOIs
StatePublished - 2 Jul 2017
Event2017 IEEE International Conference on Unmanned Systems, ICUS 2017 - Beijing, China
Duration: 27 Oct 201729 Oct 2017

Publication series

NameProceedings of 2017 IEEE International Conference on Unmanned Systems, ICUS 2017
Volume2018-January

Conference

Conference2017 IEEE International Conference on Unmanned Systems, ICUS 2017
Country/TerritoryChina
CityBeijing
Period27/10/1729/10/17

Keywords

  • coupled convolution
  • error concealment
  • image fusion
  • super resolution
  • unmanned aerial vehicles

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