中文摘要：

导弹发动机内表面自动检测系统属智能检测技术的应用研究，是应用计算机图像处理技术，实现高精度、高效率的自动无损检测。图像滤波的目的是为了去除图像中的噪声，为下一步的自动检测作准备。基于小波分析理论，构造一种既能降低图像噪声，又能够保持图像细节信息的小波去噪算法，在采用小波变换方法对图像进行滤波的同时选择基于小波分解系数阈值量化的方法进行去噪。实验结果表明该方法优于中值和均值滤波方法，因为该方法可将高频部分的空间细化，低频部分的频率细分，并能实现对图像的自适应分析，噪声去除率可达到97％。

英文摘要：

The defects detection system on missile engine＇s inner surface is the application of intelligent detection technology. It is the use of image processing technology,and it can achieve high-precision,high-efficiency and automated NDT. Image filter is designed to remove the noise in our real images, for the next stage of preparation for edge detection. A wavelet transform method to remove noise is presented based wavelet transform theory. The method can not only remove noise but also keep the detail information in images;in the same time wavelet coefficients and threshold value are chosen to remove the noise. The experimental results show the method based on wavelet transform is better than the median filtering,the average filtering method. This is because wavelet transform can breakdown high frequency part in space and low-frequency part in time. In addition,it can achieve the right adaptive image analysis ,and the rates of removing noise can reach 97%.