一种更新提升形态小波图像去噪算法

Image denoising algorithm based on the updating-lifting morphological wavelet

提出了一种新的构造非线性更新提升形态小波的方法.它利用细节信号的信息改进尺度信号,并且可以保证该小波变换具有完备重构特性.对更新提升形态小波中的更新算子进行了拓展,提出了广义更新算子,它由一系列对细节信号空域滤波的数学形态学算子综合构成.将采用了广义更新算子的更新提升小波应用于图像去噪,对比实现结果表明,与传统小波阈值去噪方法相比,该提升形态小波具有更好的去噪性能,细节图像中的边缘损失很小,尤其在低信噪比情况下性能更加优越.

A new method for constructing the nonlinear update-lifting morphologic wavelet is presented. The information of the detail signal is used to modify the scale signal, which also guarantees the perfect reconstruction feature of wavelet transform. The update operator of the update-lifting morphologic wavelet is extended. The generalized update operator is presented, which consists of a series of mathematical morphologic operators filtering the detail signals in spatial space. The update-lifting wavelet using generalized update operators is applied to image denoising. Experimental results show that the lifting morphologic wavelet has better denoising performance and less edge loss in detail image compared to the traditional wavelet thresholding method, specially in a low signal to noise ratio.