一种雾天彩色图像复原快速方法研究

暗通道优先法则在处理自然雾天图像方面取得了非常好的效果,但是该方法需要消耗大量的存储和计算时间。提出了一种改进的雾天彩色图像增强快速方法。首先,根据雾天图像模型和先验知识,计算雾天图像的暗通道先验值;并估算初始透射率图像和大气光。然后利用数学形态学方法对初始透射率图像进行处理得到优化的透射率图;并根据这个优化透射率图、大气光和原始雾天图像计算去雾图像。最后利用gama校正获得最终的彩色增强图像。仿真实验结果表明本文提出的方法能较好地对雾天彩色图像进行去雾处理,且计算速度较快。相比于基于暗原色先验的单一图像去雾方法,图像尺寸越大,该方法的计算效率越高,计算时间优势越明显。

A Fast Restoration Method for Foggy Color Image

Dark Channel Prior has made significant progress in natural color image dehazing, but its computation cost is huge. A fast method of foggy color image enhancement is proposed in this paper. Firstly, the dark channel information of the foggy image is computed according to the foggy image model and the prior knowledge, and the original transmission ratio image and the atmospheric light are estimated. Morphological method is then used to the original transmission ratio image to get a supervisor transmission ratio image, and the dehazing image can be get according to the supervisor transmission ratio image, foggy image and atmospheric light. At last, the gama adjustment is used to get the final enhancement image. The simulation results shown that the haze of color image can be removed well by using the method proposed in this paper, and computation speed is also fast. Compared with the method of single image haze removal using dark channel prior, the larger the image size is the more effective the computation of the method proposed in this paper is.