Image haze removal using a hybrid of fuzzy inference system and weighted estimation

Jyun Guo Wang, Shen-Chuan Tai, Cheng Jian Lin

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

The attenuation of the light transmitted through air can reduce image quality when taking a photograph outdoors, especially in a hazy environment. Hazy images often lack sufficient information for image recognition systems to operate effectively. In order to solve the aforementioned problems, this study proposes a hybrid method combining fuzzy theory with weighted estimation for the removal of haze from images. A transmission map is first created based on fuzzy theory. According to the transmission map, the proposed method automatically finds the possible atmospheric lights and refines the atmospheric lights by mixing these candidates. Weighted estimation is then employed to generate a refined transmission map, which removes the halo artifact from around the sharp edges. Experimental results demonstrate the superiority of the proposed method over existing methods with regard to contrast, color depth, and the elimination of halo artifacts.

Original languageEnglish
Article number033027
JournalJournal of Electronic Imaging
Volume24
Issue number3
DOIs
Publication statusPublished - 2015 May 1

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • Computer Science Applications
  • Electrical and Electronic Engineering

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