基于改进暗通道先验的太阳耀斑图像去云研究

A Cloud-removing Study of Solar Flare Images Based on Improved Dark Channel Prior

在太阳耀斑图像去云研究中,基本的暗通道先验方法存在不良效应,且其透射率优化算法过于复杂,占用空间较大。本文采用双边滤波算法对原始透射率的算法进行优化。根据标准差、熵与平均梯度这三个误差参数,将改进算法与原始的暗通道先验算法进行对比。结果显示,改进后的暗通道先验算法在太阳耀斑图像的去云方面有更好的效果。

In the study of removing cloud from solar flare images, the classic dark channel prior method has adverse effects, and its transmittance optimization algorithm is too complicated and takes up a lot of space. This paper uses a bilateral filtering algorithm to optimize the original transmittance algorithm. According to the three error parameters of standard deviation, entropy and average gradient, the improved algorithm is compared with the original dark channel prior algorithm. It is concluded that the improved dark channel prior algorithm has a better effect on the cloud removing of solar flare images.