This paper deals with an inverse problem for the unknown source term in a nonlinear evolution equation. Firstly, the authors change the initial boundary value problem (IBVP) for the equation into a Cauchy problem for a certain nonlinear evolution equation. Secondly, using the semigroup theory, the authors establish the existence and uniqueness of the solution for the inverse problem. Finally, they take advantage of the fixed point method for some contraction mapping and get the solvability of the inverse problem for the evolution equation.
为了克服正则化理论的全变分图像盲复原模型中出现的运行效率低、效果不好等问题,提出一种基于交替方向乘子法的盲复原迭代算法。该算法通过交替迭代的方式,将复原图像与点扩散函数交替估计,同时不必更新惩罚项从而提高了运行速度和复原的质量。计算同时加入了对点扩散函数的归一化和阈值约束条件以及对图像的正定性条件。数值试验中,对不同模糊类型的图像进行了盲复原处理,并与已有的其他盲复原方法进行了比较。从主观评价能够发现,提出的算法能够改进图像的质量,提高其分辨率;通过客观指标比较,峰值信噪比(peak signal to noise ratio,PSNR)最大能够提高1.2 d B,结构相似度(structural similarity index,SSIM)最大提高1%,计算时间最大节约一半左右。
