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| This paper focuses on the improvement of a newly proposed single image dehazing algorithm, Dark Channel Prior Method which is firstly proposed in paper Single Image Haze Removal Using Dark Channel Prior. The dark channel prior dehazing algorithm is based on a significant observation that in haze-free outdoor images most regions contain some pixels which have very low intensities (dark channel) in at least one color channel (RGB). Based on this observation, we can use the dark channel as the prior to directly estimate the haze thickness and recover a high quality haze-free image. Compared with other methods for single image dehazing, dark channel prior not only has better performance in situations of dense haze, but also do not rely much on significant variance on transmission and color information in the input image. Based on that, the dark channnel prior method, as a novel haze removing method, provides a simpler and more effective way for single image haze removal. Apart from that, an improvement of the original dark channel dehazing algorithm, mainly focus on removing the noise artefacts showed in the dehazed images, will be paid more attention. Through the comparison between the original and refined dark channel prior dehazing algorithm, we can see that by using the dynamic estimation algorithm on the value of t0, which is proposed in this paper, can significantly improve the dehazing performance and the dehazed image quality of the original dark channel prior dehazing algorithm. |
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| Keywords:image dehazing algorithm; dark channel prior; noise artefacts; dynamic estimation of t0 |
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