基于复小波和局部梯度的靶标图像混合降噪

Hybrid Denoising of a Target Image with Complex-valued Wavelet and Local Gradient

提出了一种有效去除光电成像测量系统中靶标图像噪音的混合降噪法.根据图像像素局部梯度模找出图像中受椒盐噪音污染的像素,使用中值滤波降噪.对去除椒盐噪音的图像,利用复对数Gabor小波提取各像素的相位信息和幅度信息,确定最小尺度滤波器对噪音幅度分布的估计值,从而自动地确定各个尺度上的噪音幅度分布的估计值和噪音萎缩阈值,达到有效降噪的目的.实验表明,该方法的降噪效果明显优于实symlet4小波、中值滤波和单一复对数Gabor小波降噪法.

A hybrid denoising method is proposed to denoise a target image efficiently in the photoelectric imaging measurement system. Pixels polluted by salt and pepper noise can be found through the comparison of their local gradient module and a threshold value, then the median filter was used to denoise. Using complex-valued log Gabor wavelet,phase information and amplitude information of a pixel can be obtained in the partially denoised image,and an estimate of noise amplitude distribution for the smallest scale filter pair can be gotten. From the statistics of the smallest scale filter response, estimates of the noise amplitude distributions at all the other scales can be obtained, and shrinkage thresholds can be set automatically. Thus the noisy image can be denoised completely. Experimental results show that the proposed method has an advantage of noise removal over the real-valued symlet4 wavelet method, the median filtering and the simplex complex-valued log Gabor wavelet method.