中文摘要：

针对实际拍摄的背景复杂、目标对比度和信噪比低的图像，在综合考滤图像去噪平滑效果、图像清晰程度和时间复杂度的基础上，提出一种基于提升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提升小波分解，再在图像高频部分进行中值滤波以改善图像的消噪效果，最后采用信噪比（SNR）与均方根误差（RMSE）和图像灰度曲面图作为图像去噪效果的评估，将提升小波变换和中值滤波相结合的图像去噪方法与小波去噪、小波与中值滤波结合消噪等进行对比实验。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，且时间度较低。

英文摘要：

Aiming at the characteristic of the actual image, which is low contrast, complex back-ground and the high background noise, a new image denoising method based on lift-wavelet analysis and median filter technology is proposed. Firstly, the noise image is decomposed with the lift-wavelet. Second, 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 denoising effect of the near-infrared 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 both can eliminate the actual image noise and maintain image edge information. It can remove effectively noise of the real images.