Imaging Components, Systems, and Processing

Image dehazing based on partitioning reconstruction and entropy-based alternating fast-weighted guided filters

[+] Author Affiliations
Yuanyu Wang

Taiyuan University of Technology, School of Computer Science and Technology, Jinzhong, China

Peter Yuen

Cranfield University, Defence Academy of UK, Shrivenham, United Kingdom

Opt. Eng. 56(5), 053111 (May 26, 2017). doi:10.1117/1.OE.56.5.053111
History: Received March 22, 2017; Accepted May 8, 2017
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Abstract.  A robust image dehazing algorithm based on the first-order scattering of the image degradation model is proposed. In this work, there are three contributions toward image dehazing: (i) a robust method for assessing the global irradiance from the most hazy-opaque regions of the imagery is proposed; (ii) more detailed depth information of the scene can be recovered through the enhancement of the transmission map using scene partitions and entropy-based alternating fast-weighted guided filters; and (iii) crucial model parameters are extracted from in-scene information. This paper briefly outlines the principle of the proposed technique and compares the dehazed results with four other dehazing algorithms using a variety of different types of imageries. The dehazed images have been assessed through a quality figure-of-merit, and experiments have shown that the proposed algorithm effectively removes haze and has achieved a much better quality of dehazed images than all other state-of-the-art dehazing methods employed in this work.

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© 2017 Society of Photo-Optical Instrumentation Engineers

Citation

Yuanyu Wang and Peter Yuen
"Image dehazing based on partitioning reconstruction and entropy-based alternating fast-weighted guided filters", Opt. Eng. 56(5), 053111 (May 26, 2017). ; http://dx.doi.org/10.1117/1.OE.56.5.053111


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