Share Email Print
cover

Proceedings Paper

An efficient video dehazing algorithm based on spectral clustering
Author(s): Fan Zhao; Zao Yao; XiaoFang Song; Yi Yao
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Image and video dehazing is a popular topic in the field of computer vision and digital image processing. A fast, optimized dehazing algorithm was recently proposed that enhances contrast and reduces flickering artifacts in a dehazed video sequence by minimizing a cost function that makes transmission values spatially and temporally coherent. However, its fixed-size block partitioning leads to block effects. Further, the weak edges in a hazy image are not addressed. Hence, a video dehazing algorithm based on customized spectral clustering is proposed. To avoid block artifacts, the spectral clustering is customized to segment static scenes to ensure the same target has the same transmission value. Assuming that dehazed edge images have richer detail than before restoration, an edge cost function is added to the ransmission model. The experimental results demonstrate that the proposed method provides higher dehazing quality and lower time complexity than the previous technique.

Paper Details

Date Published: 21 July 2017
PDF: 5 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104203T (21 July 2017); doi: 10.1117/12.2282042
Show Author Affiliations
Fan Zhao, Xi'an Univ. of Technology (China)
Zao Yao, Xi'an Univ. of Technology (China)
XiaoFang Song, Xi'an Univ. of Technology (China)
Yi Yao, Xi'an Univ. of Technology (China)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

© SPIE. Terms of Use
Back to Top