在传统太阳跟踪器的基础上结合图像处理技术，搭建一套双模式太阳跟踪器，并围绕太阳质心提取算法展开研究。针对太阳跟踪器在太阳被云雾遮挡时无法准确跟踪的问题，提出了一种基于快速中值滤波的去雾算法，根据暗通道先验计算出透射率图，使用快速中值滤波代替软抠图方法对透射率图进行平滑，还原出无雾图像。为避免人工阈值带来的分割误差，在去雾增强的图像上使用快速最大稳定极值区域(MSER)特征区域检测方法检测出太阳区域，并提取出太阳质心。实验证明该算法在雾霾天气下仍然能够还原出清晰的太阳图像，准确提取出太阳质心，并且算法复杂度较低，满足太阳跟踪器实时处理的需求。

On the basis of traditional solar tracker, a new solar tracker with double modes is built using image processing technology. The theme is focus on sun centroid extraction algorithm for solar tracker. To handle the problem that the solar tracker cannot track accurately when the sun is obscured by clouds or fogs, an image dehazing method based on rapid median filter is proposed. The transmission map is estimated by dark channel prior, and is smoothed using fast median filtering instead of soft- matting. The dehazed image is estimated using the transmission map. In order to avoid segmentation errors caused by manual threshold, an improved fast manimally stable extremal region (MSER) feature regions extraction method is proposed to extract sun area, and the centroid of the sun is computed. The experimental results indicate that the proposed algorithm can restore images captured in foggy and hazy weather, and accurately extract the centroid of the sun. The proposed method has low computational complexity and it meets the real-time processing acquirement of solar tracker.