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中文摘要：
图像恢复的根本目的是使降质图像趋向于复原或没有噪声影响的理想图像，当前的主要问题是如何在平滑噪声的同时保持图像的边缘和细节。文中提出了基于粒子群优化算法的自适应正则化参数图像恢复算法，与传统方法相比较，实验结果表明，文中方法在恢复效果上要优于传统的正则化方法、Lucy—Richardson算法和维纳（Wiener）滤波器恢复，明显地克服模糊退化，同时也保护了图像的边缘等细节信息，图像纹路更加清晰，图像质量评价的ISNR好于传统方法。
英文摘要：
The essential purpose of image restoration is to remove the noises and obtain the best estirnate of the original image. At present, a main problem is how to smooth image noise and to preserve image edge details at the same time. Presents a new approach based on particle swarm optimization to adaptively select regulation parameter. Experimental results show the propose＇d method in the paper is better than traditional methods such as regularized method, Lucy - Richardson algorithm and Wiener filtering. The proposed method clearly smoothed away the blurred image and preserved image edges. Image texture is very clear and ISNR of the proposed method is superior to those of traditional methods.
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Global attractor for the initial-boundary value problems for Ginzburg-Landau equations for atomic Fe
Global existence of solutions to the periodic initial value problems for two-dimensional Newton-Bous
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