An improved sharpening algorithm for foggy picture based on dark-channel prior
Hui Liu, Peng He · Advances in computer science research · 2015
In order to improve the clarity of degraded image in foggy weather, an improved image defogging method based on dark-channel prior is proposed.The original algorithm is sensitive to bright region and needs more computation time.An improved algorithm is proposed based on the work of previous researchers for defogging.Firstly, the sky area is adaptively selected to compute the Atmospheric light intensity.Then, fast bilateral filtering algorithm is used to refine the transmission map which greatly reduces the complexity of the algorithm.Since the color of image after haze removal is lower than the real scene, we propose a simple and effective method to adjust brightness.Experimental results indicate that the algorithm can effectively eliminate the impact of gray and bright areas on the calculations of atmospheric light and transmittance to recover the true color and clarity of the scene, while the time complexity of the algorithm is only a linear function of the input image size that can improve computing speed obviously.