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Erschienen in:
2017 | OriginalPaper | Buchkapitel
PSO-Based Single Image Defogging
verfasst von : Fan Guo, Lijue Liu, Jin Tang
Erschienen in: Computer Vision
Verlag: Springer Singapore
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Abstract
This paper proposes a novel defogging algorithm based on particle swarm optimization (PSO) to adaptively and automatically select parameter values. Owing to the lack of enough information to solve the equation of image degradation model, existing defogging methods generally introduce some parameters and set these values fixed. Inappropriate parameter setting leads to difficulty in obtaining the best defogging results for different input foggy images. In this paper, we mainly focus on the way to select optimal parameter values for image defogging. The proposed method is applied to two representative defogging algorithms by selecting the two main parameters and optimizing them using the PSO algorithm. A comparative study and qualitative evaluation demonstrate that the better quality results are obtained by using the proposed method.