中文摘要：

在DT模型、Jiang模型和LHLLAV模型等图像复原方法的基础上,提出了在新的光滑空间上的图像复原模型。首先剖析了新模型的参数含义和物理意义,阐述了Besov空间和G_（p,q）～β空间的定义、性质和范数。根据G_（p,q）～β空间和Besov空间的关系,把模型在G_（p,q）～β空间中重新描述。引入替代函数,消除K＊Ku对求解带来的困难,推导了新模型在第二代Curvelet变换域的求解,得到了一个关键性的Curvelet域收缩求解公式。最后,对图像复原模型给出了算法步骤和实验,验证了复原效果和计算复杂度,模型收敛快,比LHLLAV模型省时近一半,图像的SNR也比LHLLAV模型的高。

英文摘要：

A new smooth space image restoration model based on DT model,Jiang model,and LHLLAV model is considered.The meanings of the parameters of the new model is discussed.The definition,nature,and norm of Besov space and G_（p,q）～β space are described.The model in G_（p,q）～β space is re-described according to the relationship between G_（p,q）～β space and Besov space.By constructing a surrogate functional that removes the influence of K＊Ku,the model solution in the second generation curvelet transform domain is derived and an elegant curvelet shrinkage schemes is obtained.The experiment study shows that the new method has better restoration effect,faster convergence,and lower computational complexity than LHLLAV model.