通过观察图像lena_noise.bmp可以看到，该图像主要包含高斯噪声、椒盐噪声等。

通过查阅资料可知，维纳滤波可以很好的滤除高斯噪声，而中值滤波对于椒盐噪声的滤出效果优异，因此本次采用维纳+中值的滤波方式进行图像的去噪处理。

图像常用评价方法有：信噪比、相关系数、清晰度。信噪比较为常用；相关系数 由于滤波会使原图像失去某些细节，因此这种评价方式为参考性指标而非绝对评判标准；清晰度 为图像子块的方差

综合考虑采用图像的峰值信噪比(PSNR)作为评价去噪效果指标(自编PSNR.m函数).-By observing the image lena_noise.bmp can see that the image consists mainly of Gaussian noise, salt and pepper noise.　 Through access to information shows that the Wiener filter can be well filtered Gaussian noise, and median filter for impulse noise filter out excellent results, so this value using Wiener filtering method+ in image denoising.　 Image evaluation methods commonly used are: noise ratio, correlation coefficient, clarity. SNR is more commonly used　correlation coefficient as filtering the original image will lose some of the details, so this evaluation method as the reference index rather than absolute criteria　clarity of image sub-block variance　considering the peak signal using image noise ratio (PSNR) as an evaluation index denoising (self PSNR.m function).