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A Global-Local Approach to Extracting Deformable Fashion Items from Web Images Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Real-Time Video Dehazing Based on Spatio-Temporal MRF

Authors : Bolun Cai, Xiangmin Xu, Dacheng Tao

Published in: Advances in Multimedia Information Processing - PCM 2016

Publisher: Springer International Publishing

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Abstract

Video dehazing has a wide range of real-time applications, but the challenges mainly come from spatio-temporal coherence and computational efficiency. In this paper, a spatio-temporal optimization framework for real-time video dehazing is proposed, which reduces blocking and flickering artifacts and achieves high-quality enhanced results. We build a Markov Random Field (MRF) with an Intensity Value Prior (IVP) to handle spatial consistency and temporal coherence. By maximizing the MRF likelihood function, the proposed framework estimates the haze concentration and preserves the information optimally. Moreover, to facilitate real-time applications, integral image technique is approximated to reduce the main computational burden. Experimental results demonstrate that the proposed framework is effectively to remove haze and flickering artifacts, and sufficiently fast for real-time applications.

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previous chapter Abnormal Event Detection and Localization by Using Sparse Coding and Reconstruction
next chapter Dynamic Contour Matching for Lossy Screen Content Picture Intra Coding
Footnotes
3
More comparisons can be found at http://​caibolun.​github.​io/​st-mrf/​.
 
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Metadata
Title
Real-Time Video Dehazing Based on Spatio-Temporal MRF
Authors
Bolun Cai
Xiangmin Xu
Dacheng Tao
Copyright Year
2016
Book
Advances in Multimedia Information Processing - PCM 2016

Print ISBN: 978-3-319-48895-0

Electronic ISBN: 978-3-319-48896-7

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-48896-7_31