阈值寻优的高保真各向异性滤波模型

Anisotropic Filtering Model of High-fidelity Based on Threshold Optimization

在各向异性扩散滤波方法中,边缘检测的准确性对滤波结果有重要的影响.为了增强图像滤波的效果,提出一种阈值寻优的高保真各向异性滤波方法.首先用小波变换提取图像的高频部分,在高频部分用二阶微分量曲率模值来反映局部信息,避免将图像的尖峰、角点误认为噪声,保护图像的尖峰、角点等细节信息;然后用最小均方算法设计阈值,进一步控制扩散强度,建立新的各向异性滤波模型;最后用建立的新模型对提取的高频部分进行处理,对处理后的高频系数和原来的低频系数进行小波重构,得到去噪后的图像.实验结果表明,文中方法去噪性能优异,较好地保持了图像细节;另外,该方法的运行时间较短,有利于实际应用,是一种理想的方法.

In the anisotropic diffusion filtering method, the accuracy of edge detection has an important influence on the filtering results. In order to enhance the image filtering effect, this paper put forward a novel anisotropic filtering method of high-fidelity based on threshold optimization. Firstly, wavelet is used to extract image high frequency part, second-differential modulus is used to express local information, this will avoid mistaking peak and corner for noise, and image local information will be saved. Then, least mean square algorithm is used to design a threshold, it will control the diffusing strength, and the novel anisotropic model will be established. Last, the novel model is used to process the high-frequency, and wavelet is used to reconstruct denoised image with the processed high frequency part and original low frequency part. Experiment results indicate that the novel method has a perfect performance, it can protect image details well. Moreover, the running time of the proposed method is relatively short, it is applicable, so the proposed method is ideal.