Infrared image enhancement based on Riemann-Liouville fractional calculus and human visual properties

Kai Zhang, Qun Hao, Yong Song, Yao Hu

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

1 Citation (Scopus)

Abstract

In order to improve the definition of the infrared image, and make it more accessible for human eyes, an infrared image enhancement algorithm based on Riemann-Liouville (R-L) fractional calculus and human visual properties is proposed in this paper. Combining the mathematical model of human retinal receptive field with R-L fractional calculus theory, an R-L fractional order Rodieck enhancement mask is designed. The mask is used to enhance the textures and edges of the image. Then, the grayscales of the enhancement result are adjusted according to the grayscale resolution capabilities of human eyes. It further improves the contrast of infrared images. Experimental results show that the proposed algorithm can effectively enhance the texture details and contrast of infrared images. Compared with histogram equalization method and multi-Retinex method, the enhancement result of the proposed algorithm has better visual effect, and it is more accessible for human eyes.

Original languageEnglish
Title of host publicationInternational Symposium on Photoelectronic Detection and Imaging 2013
Subtitle of host publicationInfrared Imaging and Applications
PublisherSPIE
ISBN (Print)9780819497765
DOIs
Publication statusPublished - 2013
Event5th International Symposium on Photoelectronic Detection and Imaging, ISPDI 2013 - Beijing, China
Duration: 25 Jun 201327 Jun 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8907
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference5th International Symposium on Photoelectronic Detection and Imaging, ISPDI 2013
Country/TerritoryChina
CityBeijing
Period25/06/1327/06/13

Keywords

  • fractional calculus
  • human visual properties
  • image enhancement
  • infrared image processing

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