自适应阈值的小波变换在纸病去噪中的应用

The application of adaptiving with threshold wavelet transform in the defect denoising

以图像噪声会影响下一步图像处理、分析及识别为启示,分析了常用的数字滤波算法优缺点,提出一种自适应阈值小波变换去噪方法.该方法根据含噪信号特性和信噪比,自适应地选择小波变换的最优分解层数和最佳软阈值,达到最优的降噪效果.仿真结果表明,这种算法在高斯噪声和椒盐噪声滤波能有效地滤除噪声,同时还能较好地保护图像细节,使图像达到更好的视觉效果.

This paper proposed an improvement method based on adaptive with threshold wavelet transform denoising algorithm, the noise will affect the next step of image process- ing, analysis and recognition for inspiration, compared with the advantages and disadvanta- ges of traditional digital filtering method. According to noisy signal characteristics and SNR, it can adaptively select wavelet transform of optimal decomposition level and soft threshold to achieve the optimal noise reduction effect. The gray of the defect image is smoothed, en- hancement, edge extraction, filtering, recovery. The Simulation results demonstrate that this theory can effectively filtering Gaussian noise and Salt and pepper noise, at the same time well protect the image details and achieve better visual effects.