A sparse signal representation-based image denoising algorithm for uncooled MEMS IRFPA

  • Liquan Dong*
  • , Xiaohua Liu
  • , Yuejin Zhao
  • , Ming Liu
  • , Mei Hui
  • , Xiaoxiao Zhou
  • *Corresponding author for this work

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

1 Citation (Scopus)

Abstract

An uncooled thermal detector array with low NETD is designed and fabricated using MEMS bimaterial microcantilever structures that bend in response to thermal change. The IR images of objects obtained by these FPAs are readout by an optical method. For the IR images, processed by a sparse representation-based image denoising and inpainting algorithm, which generalizing the K-Means clustering process, for adapting dictionaries in order to achieve sparse signal representations. The processed image quality is improved obviously. Great compute and analysis have been realized by using the discussed algorithm to the simulated data and in applications on real data. The experimental results demonstrate, better RMSE and highest Peak Signal-to-Noise Ratio (PSNR) compared with traditional methods can be obtained. At last we discuss the factors that determine the ultimate performance of the FPA. And we indicated that one of the unique advantages of the present approach is the scalability to larger imaging arrays.

Original languageEnglish
Title of host publicationInfrared Systems and Photoelectronic Technology III
DOIs
Publication statusPublished - 2008
EventInfrared Systems and Photoelectronic Technology III - San Diego, CA, United States
Duration: 10 Aug 200812 Aug 2008

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7055
ISSN (Print)0277-786X

Conference

ConferenceInfrared Systems and Photoelectronic Technology III
Country/TerritoryUnited States
CitySan Diego, CA
Period10/08/0812/08/08

Keywords

  • Image denoising
  • MEMS
  • Optical readout
  • Sparse signal representation
  • Un-cooled IR

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