中文摘要：

针对某些图像中背景复杂、目标对比度和信噪比低等特点，提出一种基于小波变换和中值滤波的图像去噪方法。首先对含噪图像进行小波分解，再在图像高频部分进行中值滤波以改善图像的消噪效果，最后将信噪比（SNR）与均方根误差（RMSE）和图像灰度曲面图等作为图像去噪效果的评估，通过小波变换和中值滤波相结合的图像去噪方法与小波去噪、中值滤波消噪等的对比实验，结果表明，该方法既能消除图像噪声又能达到保持其图像边缘要求，但在仿真计算时，其计算量较大。

英文摘要：

Based on the characteristics of some images, such as low contrast, complex back-ground and the high background noise, a new image de- noising method based on wavelet -analysis and median filter technology is proposed. Firstly, the noise image is decomposed with the wavelet - analysis. Secondly, the high frequency parts of decomposed image are carried on median filter algorithm to improve the removing result of the noise image. The denoising image is obtained to reconstruct the high frequency parts processed and low frequency parts of decomposed image. Finally, the image signal to noise ratio （SNR） and the root - mean - square error （RMSE） and the image gray surface chart are applied to estimate the de - noising effect of the images. These removing noise methods, such as the ordinary wavelet filter, the median filter and so on, are applied to remove the image noises. The experimental results indicate that this method can not only ,eliminate the image noise but also maintain image edge information. It can remove effectively the noise of the real images.