摘要
雾天条件下采集的图像存在低对比度和低场景可见度问题,传统的去雾算法时间复杂度高、速度慢,无法应用于实时图像处理。为此,结合大气光特性提出一种改进的基于均值滤波的单幅图像复原方法。该方法以大气散射模型为基础,首先利用均值滤波得到准确的大气耗散函数;引入直方图修正机制下的自适应保护因子,更正明亮区域的大气散射函数;大气光采用效率更高的四叉树算法求解;最后由大气散射模型计算复原图像并进行图像的亮度调整,从而得到一幅清晰的无雾图像。仿真实验结果表明:该算法的场景适应能力强,复原图像色彩感丰富。与经典的去雾算法相比,该算法在保证去雾效果的同时,克服了导向滤波算法时间复杂度高、速度慢的缺陷。
In foggy conditions, acquired images have low contrast ratio and low scene visibility problems. The traditional defogging algorithm has high time complexity with low speed characteristics and can not be applied in real-time image processing. Thus, a single image restoration method based on mean filter is proposed in this paper combined with the optical properties of atmospheric. In this method, on the basis of atmospheric scattering model, accurate atmospheric dissipation function can be achieved firstly using mean filter. The adaptive histogram correction mechanism under the protection factor is introduced to correct atmospheric scattering function in bright areas. Atmosphere light is obtained by quadtree algo- rithm which is more efficient. Finally, restored image is calculated by the atmospheric scattering model and the brightness of the image is adjusted, and a clear image without fog is obtained. Simulation results show that this algorithm has a strong adaptability to various scenes and restored images have plentiful colors. Compared with the classic defogging algorithm, this algorithm ensures the defogging effect while overcomes the high time complexity and low speed defects of guide filter algorithm.
出处
《西安科技大学学报》
CAS
北大核心
2016年第4期583-588,共6页
Journal of Xi’an University of Science and Technology
基金
陕西省科技攻关计划(2012K06-16)
陕西省自然科学基金(2015JQ6221
2016JQ6064)
关键词
图像去雾
均值滤波
导向滤波
大气耗散函数
image defogging
mean filter
guide filter
atmospheric dissipation function
