Haze effect removal from image via haze density estimation in optical model

Chia Hung Yeh, Li Wei Kang, Ming Sui Lee, Cheng Yang Lin

Research output: Contribution to journalArticlepeer-review

Abstract

Images/videos captured from optical devices are usually degraded by turbid media such as haze, smoke, fog, rain and snow. Haze is the most common problem in outdoor scenes because of the atmosphere conditions. This paper proposes a novel single image-based dehazing framework to remove haze artifacts from images, where we propose two novel image priors, called the pixel-based dark channel prior and the pixel-based bright channel prior. Based on the two priors with the haze optical model, we propose to estimate atmospheric light via haze density analysis. We can then estimate transmission map, followed by refining it via the bilateral filter. As a result, high-quality haze-free images can be recovered with lower computational complexity compared with the state-of-the-art approach based on patch-based dark channel prior.

Original languageEnglish
Pages (from-to)27127-27141
Number of pages15
JournalOptics Express
Volume21
Issue number22
DOIs
Publication statusPublished - 2013 Nov 4
Externally publishedYes

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

Fingerprint

Dive into the research topics of 'Haze effect removal from image via haze density estimation in optical model'. Together they form a unique fingerprint.

Cite this