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A GPU-accelerated real-time single image de-hazing method using pixel-level optimal de-hazing criterion

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Abstract

Single image de-hazing is an important and challenging research topic in computer vision. The computational efficiency and robustness of this issue are key problems in real-time applications. In this paper, a graphic processing unit (GPU)-accelerated real-time image enhancing method is proposed to remove haze from a single hazy input image. The foundation of this method is a novel pixel-level optimal de-hazing criterion proposed to combine a virtual hazy-free candidate image sequence into a final single hazy-free image. This image sequence is estimated from the input hazy image by exhausting all possible discretely sampled scene depth values. The main advantage of proposed method is the single pixel independently computing fashion. Its computing at one single pixel position is independent of others. Based on this property, it is straightforward to implement the proposed method with fully parallel GPU acceleration. The sufficient experimentations on various scenes indicate that the proposed method can process a large hazy image with one megapixel to visually moderate haze-free result at a rate of 80 frames/s. Moreover, the proposed method is also less affected by the nonuniform illumination compared to previous methods.

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Acknowledgments

This paper is jointly supported by the National Natural Science Foundation of China (Project No. 61074106) and China Aviation Science Foundation (Project No. 2009ZC57003).

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  1. School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China

    Jun Zhang & Shiqiang Hu

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  1. Jun Zhang
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  2. Shiqiang Hu
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Correspondence to Jun Zhang.

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Zhang, J., Hu, S. A GPU-accelerated real-time single image de-hazing method using pixel-level optimal de-hazing criterion. J Real-Time Image Proc 9, 661–672 (2014). https://doi.org/10.1007/s11554-012-0244-y

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  • DOI: https://doi.org/10.1007/s11554-012-0244-y

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