基于状态权的小波边缘检测算法

提出了一种基于小波变换和各向异性扩散的图像多尺度边缘检测方法。对噪声图像进行小波变换,得到高频和低频小波系数。对高频小波系数归一化后进行各向异性扩散得到状态权,把该权值作用在原高频小波系数上,得到了既去除噪声又保持结构不变的小波系数。对低频小波系数直接用小波阈值方法去噪,利用小波系数模极大值法对去噪后的高频和低频小波系数进行边缘检测,得到最终的边缘图像。实验结果表明,该边缘检测方法由于结合了小波和各向异性扩散方法,从而有效地抑制了噪声,得到了连续、清晰的边缘。

Wavelet edge detection method based on state weights.

Edge detection based on wavelet and anisotropic diffusion is proposed.It should be carried out the way the denoising image is decomposed by wavelet so as to gain high frequency and low frequency wavelet coefficients.Anisotropic diffusion method is used to achieve state weights after the high frequency wavelet coefficients are normalized.The new higher frequency wavelet coefficients both to remove noise and keep the structure unchanged are achieved when state weights act on original wavelet coefficients.The low frequency wavelet coefficients are denoised by means of wavelet threshold.The high frequency and low frequency wavelet coefficients are detected through detecting the local maximum of the wavelet transformation coefficient modulus.The final edge images are obtained.Owing to introducing the mixed method of combining wavelet with anisotropic diffusion,it is indicated from the experimental result that the noises are restrained efficiently and the edges are consecutive and clear.