Optimizing Coded Patterns with Various Lengths

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

Abstract

The performance of coded exposure photography-based image deblurring highly depends on its coded pattern to use. Conventionally, the length of the coded pattern has been optimized under the assumption that its length is equal to the length of motion blur. However, coded patterns of different lengths from the same motion blur may have better invertibility than the conventional patterns. In this paper, we investigate a method to optimize the coded pattern within an extended range of length candidates. We demonstrate the effectiveness of the proposed method using a real dataset.

Original languageEnglish
Title of host publicationInternational Workshop on Advanced Imaging Technology, IWAIT 2022
EditorsMasayuki Nakajima, Shogo Muramatsu, Jae-Gon Kim, Jing-Ming Guo, Qian Kemao
PublisherSPIE
ISBN (Electronic)9781510653313
DOIs
StatePublished - 2022
Externally publishedYes
Event2022 International Workshop on Advanced Imaging Technology, IWAIT 2022 - Hong Kong, China
Duration: 4 Jan 20226 Jan 2022

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12177
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference2022 International Workshop on Advanced Imaging Technology, IWAIT 2022
Country/TerritoryChina
CityHong Kong
Period4/01/226/01/22

Keywords

  • Computational photography
  • image deconvolution
  • motion deblurring

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