Visibility Restoration of Single Hazy Images Captured in Real-World Weather Conditions
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- 16 April 2014
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Circuits and Systems for Video Technology
- Vol. 24 (10), 1814-1824
- https://doi.org/10.1109/tcsvt.2014.2317854
Abstract
The visibility of outdoor images captured in inclement weather is often degraded due to the presence of haze, fog, sandstorms, and so on. Poor visibility caused by atmospheric phenomena in turn causes failure in computer vision applications, such as outdoor object recognition systems, obstacle detection systems, video surveillance systems, and intelligent transportation systems. In order to solve this problem, visibility restoration (VR) techniques have been developed and play an important role in many computer vision applications that operate in various weather conditions. However, removing haze from a single image with a complex structure and color distortion is a difficult task for VR techniques. This paper proposes a novel VR method that uses a combination of three major modules: 1) a depth estimation (DE) module; 2) a color analysis (CA) module; and 3) a VR module. The proposed DE module takes advantage of the median filter technique and adopts our adaptive gamma correction technique. By doing so, halo effects can be avoided in images with complex structures, and effective transmission map estimation can be achieved. The proposed CA module is based on the gray world assumption and analyzes the color characteristics of the input hazy image. Subsequently, the VR module uses the adjusted transmission map and the color-correlated information to repair the color distortion in variable scenes captured during inclement weather conditions. The experimental results demonstrate that our proposed method provides superior haze removal in comparison with the previous state-of-the-art method through qualitative and quantitative evaluations of different scenes captured during various weather conditions.Keywords
Funding Information
- National Science Council (NSC 100-2628-E-027-012-MY3, NSC 102-2221-E-027-065)
This publication has 13 references indexed in Scilit:
- A Novel Visibility Restoration Algorithm for Single Hazy ImagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- Hardware Implementation of a Fast and Efficient Haze Removal MethodIEEE Transactions on Circuits and Systems for Video Technology, 2013
- Underwater Image Enhancement by Wavelength Compensation and DehazingIEEE Transactions on Image Processing, 2011
- Single Image Haze Removal Using Dark Channel PriorIEEE Transactions on Pattern Analysis and Machine Intelligence, 2010
- Deep photoACM Transactions on Graphics, 2008
- BLIND CONTRAST ENHANCEMENT ASSESSMENT BY GRADIENT RATIOING AT VISIBLE EDGESImage Analysis and Stereology, 2008
- Removing weather effects from monochrome imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Contrast restoration of weather degraded imagesIEEE Transactions on Pattern Analysis and Machine Intelligence, 2003
- Polarization-based vision through hazeApplied Optics, 2003
- Formal connections between lightness algorithmsJournal of the Optical Society of America A, 1986