NDLI: Fast smoothing technique with edge preservation for single image dehazing

Content Provider	IET Digital Library
Author	Wang, Dan Zhu, Jubo
Abstract	In the single-image dehazing problem, it is critical that the transmission is accurately estimated. However, the extracted transmission in the dark channel model cannot effectively deal with the edge and the sky area because of the poor applicability of the dark channel prior to these areas. This study aims to solve that problem by proposing a novel variational model (VM) to optimise the transmission. This VM introduces a smoothness term and a gradient-preserving term to mitigate the false edge and the distorted sky area in the recovered image. Further, a fast algorithm to solve the VM is proposed on the basis of the additional operator splitting algorithm. This algorithm is an effective linear time algorithm and has excellent performance on optimising the transmission. The average running time of the algorithm shows an improvement of over 20 times that of the guided image filtering in these experiments. Experimental results also show that the proposed algorithm is both effective and efficient for optimising the transmission.
Starting Page	950
Ending Page	959
Page Count	10
ISSN	17519632
Volume Number	9
e-ISSN	17519640
Issue Number	Issue 6, Dec (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/9/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2015.0063
Journal	IET Computer Vision
Publisher Date	2015-12-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Additional Operator Splitting Algorithm Computational Complexity Computer Vision And Image Processing Technique Distorted Sky Area Mitigation Edge Detection Edge Preservation False Edge Mitigation Gradient Preservation Guided Image Filtering Image Filtering Linear Time Algorithm Optical, Image And Video Signal Processing Optimisation Optimisation Technique Single Image Dehazing Smoothing Method Smoothing Technique Smoothness Transmission Optimisation Variational Model Variational Technique VM
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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