非凸混合总变分图像盲复原

Non-convex hybrid total variation method for image blind restoration

为实现模糊噪声图像的盲复原,提出了一种混合非凸总变分和高阶总变分的多正则化约束的图像盲复原方法.首先,根据自然图像边缘的稀疏特性,运用了非凸总变分对复原图像进行正则化约束;然后,结合高阶总变分正则化克服阶梯效应的优势,建立了非凸混合总变分极小化模型;最后,利用增广拉格朗日方法和新的广义p收缩算子对提出的模型进行最优化求解.实验结果表明,提出的方法能够有效保护图像边缘细节,同时消除了图像平滑区域的阶梯效应,获得高质量的复原图像.

A multi-regularization constraint method for imageblind restoration is proposed to recover the blurry-noisy images.First,the non-convex total variation is adoptedas the regularization constraint by taking the sparse edges in the natural image into consideration.Next,the high-order total variation is used to overcome the staircase effects in the smooth regions of the image.Then a non-convex minimization model is proposed.Finally,the augmented Lagrangian method and a new generalized p shrinkage operator are applied to solve the model.The results of numerical experiments show that the proposed method can preserve the image edges while removing the staircase effects effectively.The high quality restored image can be obtained.