Text-aware image dehazing using stroke width transform

Jinwon Park, Kyumok Kim, Sungmin Lee, Chee Sun Won, Seung Won Jung

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

5 Scopus citations

Abstract

Haze removal, which is also referred to as image dehazing, has been extensively used to improve the visibility in images captured under inclement weather. In particular, the dark channel prior (DCP)-based single image dehazing has received the greatest amount of interest due to its superior performance. However, since the DCP is based on the characteristics of natural outdoor images, its reliability tends to decrease especially when an image contains man-made textures. In this paper, we present a DCP-based single image dehazing method that is robust when text or text-like patterns are present in the image. The proposed method first estimates the text likelihood from a hazy image using the stroke width transform (SWT) and uses the estimated likelihood to correct the DCP. The experimental results show that the proposed algorithm outperforms the conventional DCP-based dehazing methods.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PublisherIEEE Computer Society
Pages2231-2235
Number of pages5
ISBN (Electronic)9781467399616
DOIs
StatePublished - 3 Aug 2016
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: 25 Sep 201628 Sep 2016

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2016-August
ISSN (Print)1522-4880

Conference

Conference23rd IEEE International Conference on Image Processing, ICIP 2016
Country/TerritoryUnited States
CityPhoenix
Period25/09/1628/09/16

Keywords

  • Dark channel prior
  • Haze removal
  • Image dehazing
  • Stroke width transform

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