EMCCD图像自适应模糊中值滤波算法研究

针对电子倍增CCD（EMCCD）图像噪声密度随着增益的变化而变化，提出了一种基于噪声点检测的自适应模糊中值滤波算法。该算法由模糊滤波模块和自适应模块两部分组成。首先，该算法对滤波窗口内的中心点进行噪声检测；然后对检测为噪声的像素点引入双阈值，并根据引入的阈值和滤波窗口内的中值建立噪声点的模糊隶属函数，根据模糊隶属函数对噪声点进行滤波处理后输出；最后采用自适应模块调整待处理图像的像素。仿真及实验结果表明，新算法不仅能够有效地将图像中的噪声去除，而且很好地保护了图像中的细节和边缘，PSNR比传统的自适应中值滤波算法平均提高了15 dB以上；该算法在低噪声密度情况下性能明显好于其他中值滤波器，在高噪声密度情况下性能也比较稳定。

Research of EMCCD image filtering method based on adaptive fuzzy median filter

The noise density of Electron Multiplying CCD(EMCCD) image varies with the gain, a noise detection based on adaptive fuzzy median filter(AFMF) algorithm was proposed. The algorithm consisted of fuzzy filtering module and adaptive module. First, the noise pixels in the center of the filter window was identified. Second, the double thresholds were introduced for these detected noise points, basing on the thresholds and median of the filtering window, the fuzzy membership function of noise points was put forward, and the fuzzy membership function was utilized to filter the noise points. Finally, the adaptive module was used to adjust the pixel in the image. Simulation and experimental results indicate that the new algorithm is able to remove noise pixels effectively and protect the details well in the image. Compared with the adaptive median filtering, the average PSNR improves at least 15 dB. The performance is better than the other median filters under the condition of low noise density and relatively stable under the condition of high noise density.