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Erschienen in:
2014 | OriginalPaper | Buchkapitel
A Fast Algorithm for Image Defogging
verfasst von : Xiaoyan He, Jianxu Mao, Zewen Liu, Jiujiang Zhou, Yajing Hua
Erschienen in: Pattern Recognition
Verlag: Springer Berlin Heidelberg
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In smoke and haze environment, images acquired by vision create serious distortion or degradation. Obtaining some inaccurate information from an unclear vision, it will have some bad impacts on outdoor activities. More and more common in recent years, the haze phenomena need to be further research. According to the images analysis of the atmospheric degradation model, this article puts forward the improved algorithm based on dark channel prior and morphology. Given the application of He’s algorithm to defog, it makes brightness reduce. Therefore, the article firstly proposes to increase the brightness of image before processing, and then estimates the global atmospheric value, the initial transmission rate and the haze density using morphology method, finally substitutes into the simplified model to get the haze-free image. The experimental results show that the proposed algorithm can recover effectively and quickly degraded images. Meanwhile, this algorithm can keep the detail edges of images.