基于Garrote阈值法去噪的改进研究

Research on the Improvement of Denoising Based on Garrote Threshold Method

针对传统Garrote阈值函数采用固定阈值收缩高频细节系数,并对高频细节系数进一步收缩方面缺乏统一有效手段的问题,本文提出了一种基于传统Garrote阈值法的改进去噪方法。该改进方法既能兼顾各尺度下的不同阈值,又能进一步收缩高频细节系数,并且易于实现、计算简单。在高斯白噪声去噪方面,去噪后的图像在均方差(MSE)和峰值信噪比(PSNR)上,均优于传统Garrote阈值法。

Against the traditional Garrote threshold function which used fixed threshold to shrink high frequency detail coefficients,and which had the problem which lacked unified and effective method to shrink high frequency detail coefficients further,this paper proposed an improved de-nosing method based on traditional Garrote threshold method. This improved method can take into account the different thresholds at different scales,and can shrink high frequency detail coefficients further.And this method implemented easily,calculated simply. For the Gaussian white noise de-noising,the de-nosing image which used this paper＇s method exceeded the traditional Garrote threshold at the in mean square（MSE）and peak signal to noise ratio（PSNR）.