一种图像去模糊正则化恢复算法参数确定方法

摘要

为了解决模糊正则化恢复算法中参数确定问题,提出一种正则化参数确定方法,该方法根据降质图像特征计算正则化参数.分析了目前普遍应用的全变分正则化方法和该问题的改进拉格朗日迭代解法(SALSA),分析不同正则化参数对恢复效果的影响,提出的正则化参数确定方法与噪声和原图像梯度大小相关.对不同梯度和噪声图像的不同正则化参数恢复效果进行对比,得到提出的正则化参数确定方法能使恢复图像的改进信噪比处于最大值附近.从实验视觉效果得出,该参数确定方法能够抑制降质图像的噪声并能够尽量恢复原图像细节信息.%A method of determining the regularization parameter is proposed in order to solve the image deblurring problems. The main objective is to get the regularization parameter from the deblurring image. The method starts by considering the famous Total Variation methods and the Split Augmented Lagrangian Shrinkage Algorithm (SALSA) , and then it deals with the effect of the regularization parameter on the result image. The proposed method proves that the parameter is determined by the noise and the gradient of the image. Results of the recovery of images were compared with different gradient and noise, and they help to reach a conclusion that the proposed method maximizes the improvement in Signal to Noise Ratio (ISNR). The method also removed noise and protected the details of the image in the processing of recovery as much as possible.