基于双边滤波与小波变换的分频滤波算法的分析

Frequency Filtering Algorithm Research Based on Bilateral Filtering and Second-generation Wavelet Transform

针对图像在滤波时把图像的一些特征信息去除和图像分割边缘模糊的问题,提出了基于双边滤波和小波变换的分频滤波算法.通过二代小波提升变换后,得到图像的高频分量和低频分量,然后结合双边滤波和小波变换各自的优缺点,在低频分量部分采用双边滤波,在高频分量部分采用阈值小波变换,通过Matlab仿真结果分析,该方法在滤波过程中有很明显的优势.

Aiming at the problem that some of the feature information of the image is removed and the edge of the image is blurred when filtering, a frequency filtering algorithm based on bilateral filtering and wavelet transform is proposed. After the second-generation wavelet lifting transform, the high-frequency components and low-frequency components of the image are obtained. Then, the advantages and disadvantages of the two-sided filtering and wavelet transform are combined. Binary filtering is used in the low frequency component, and the threshold wavelet transform is adopted in the high frequency component. Simulation results show that this method has obvious advantages in the filtering process.