Shannon小波包分解自适应Gabor滤波器设计及其在纹理分割中的应用

本文首先研究了Ｇａｂｏｒ滤波器进行确定性纹理分割时纹理结构与Ｇａｂｏｒ函数的关系，提出了利用在频域中具有紧支集的Ｓｈａｎｎｏｎ小波包分解检测纹理的主频；最后，提出了基于小波包分解自适应Ｇａｂｏｒ函数与纹理图像卷积，就可以在纹理的连续处产生良好的阶跃边缘，并通过实验验证了该算法的有效性及其对噪声的鲁棒性。

Shannon小波包分解自适应Gabor滤波器设计及其在纹理分割中的应用

In this peper. the relationship of the texture structure and Gabor filter is studied at first.then it is given out that using Shannon wavelet packets with compact support in frequency domain to detect the texture main frequency.Next. the method of designing wavelet packets decomposition adaptive Gabor function to segment texture algorithm is given out. This algorithm firstly Applies the texture main frequency detected by Shannon wavelet decomposition to design Gabor filter and then uses Gabor filter to convolute with the original texture image. The algorithm can produce very good step edge at the joining place of two textures joining. The experiment results show that the algorithm is very efficient and robust to noise.