Dark image enhancement based onpairwise target contrast and multi-scale detail boosting

Youngbae Kim, Yeong Jun Koh, Chulwoo Lee, Sehoon Kim, Chang-Su Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

A dark image enhancement algorithm based on the pairwise target contrast and the multi-scale detail boosting is proposed in this work. We first compute the pairwise target contrast between a pair of pixels, which represents the desired gray level difference of the two pixels in the output image. By aggregating the pairwise target contrasts for all pairs of pixels in an image, we formulate a cost function for the enhancement. By minimizing the cost function, we obtain the optimal transformation function and enhance the image. In addition, we propose a multi-scale approach to boost details in the globally enhanced image. Experimental results show that the proposed algorithm enhances the contrast and visibility of dark images more effectively than conventional algorithms.

Original languageEnglish
Title of host publicationProceedings - International Conference on Image Processing, ICIP
PublisherIEEE Computer Society
Pages1404-1408
Number of pages5
Volume2015-December
ISBN (Print)9781479983391
DOIs
Publication statusPublished - 2015 Dec 9
EventIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
Duration: 2015 Sep 272015 Sep 30

Other

OtherIEEE International Conference on Image Processing, ICIP 2015
CountryCanada
CityQuebec City
Period15/9/2715/9/30

Keywords

  • backlit image enhancement
  • contrast enhancement
  • Dark image enhancement
  • multi-scale detail boosting
  • pairwise target contrast

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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  • Cite this

    Kim, Y., Koh, Y. J., Lee, C., Kim, S., & Kim, C-S. (2015). Dark image enhancement based onpairwise target contrast and multi-scale detail boosting. In Proceedings - International Conference on Image Processing, ICIP (Vol. 2015-December, pp. 1404-1408). [7351031] IEEE Computer Society. https://doi.org/10.1109/ICIP.2015.7351031