一种基于粒子群优化算法的图像盲复原方法

传统的图像盲复原算法通常采用模糊图像与复原图像的均方误差作为优化的性能指标.为进一步提高复原效果,结合反映人类视觉特性的Weber定律,提出一种改进的图像盲复原优化性能指标,并且采用双粒子群交替最小化进行求解,即在模糊辨识阶段,采用一个粒子群优化算法求解点传播函数;在复原阶段,采用另一个粒子群优化算法求解复原图像.仿真实验表明,提出的算法比以前的算法有更好的复原效果.

A PSO-based Method for Blind Image Restoration

Mean Square Error(MSE) between the fuzzy image and restoration image is usually used as criterion in the traditional blind image restoration methods. In order to get finer restoration image,a modified blind image restoration criterion is presented in this paper,which combing with the model of visual characteristic(Weber's law).In addition,based on two Particle Swarm Optimizers(PSO),an iterative scheme using alternating minimization is devised to recover the image and simultaneously identify the Point Spread Function(PSF).The first PSO focus on evolving PSF in the process of identification.At the same time,the second PSO focus on evolving the recover image in the process of restoration.The results of experiments show a superior performance compared to the previous approach.