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Fast curvelet transform based non-uniformity correction for IRFPA

  • Beijing Institute of Technology

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

Abstract

The Curvelet transform was developed from the wavelet transform. The applications of Curve-let transform reveal its great potential in image processing due to its unique characteristics. In this paper, the theory and implementation of Curvelet transform is summarized. The traditional Curvelet transform involves a complicated index structure which makes the mathematics and quantitative analysis especially delicate, and it uses overlapping windows increasing the redundancy. The Fast Curvelet Transform was discussed in this paper, which has the optimal sparse representation. By utilizing Curvelet wrapping algorithm based on translation invariance to the nonuniformity correction of the IRFPA, better MSE compared with traditional methods can be obtained. Great compute and analysis have been realized by using the discussed algorithm to the simulated data and real infrared scene data respectively. The experimental results demonstrate, the corrected image by this fast Curvelet transform algorithm not only yields highest Peak Signal-to-Noise Ratio values (PSNR = 33.803), but also achieves best visual quality.

Original languageEnglish
Title of host publicationInfrared Materials, Devices, and Applications
DOIs
Publication statusPublished - 2007
EventInfrared Materials, Devices, and Applications - Beijing, China
Duration: 12 Nov 200715 Nov 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6835
ISSN (Print)0277-786X

Conference

ConferenceInfrared Materials, Devices, and Applications
Country/TerritoryChina
CityBeijing
Period12/11/0715/11/07

Keywords

  • Curvelet transform
  • IR focal plane array
  • Non-uniformity correction

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