基于改进卡尔曼滤波的盲图像恢复

Blind image restoration based on improved Kalman filter

为了解决在获取数字图像过程中发生的图像质量下降(退化)的问题,需要使用图像恢复技术进行图像重建。针对未知点扩散函数(PSF)的盲图像恢复,首先利用倒频谱的方法估计模糊图像的点扩散函数,然后再利用改进的卡尔曼滤波方法对图像进行恢复。倒频谱方法是将模糊图像分成反映原图像信息和反映模糊系统信息的两部分相加的形式,通过分析两者的关系估计出模糊图像的PSF。改进卡尔曼滤波器在估计过程中考虑了系统的模型误差,使其对模型误差具有一定的鲁棒性。通过M atlab进行了数字仿真实验,实验结果表明利用所提出的方法可以有效地减小PSF估计不准确对图像恢复的影响,与传统卡尔曼滤波相比恢复效果较好。

To eliminate or reduce the image degradation, the image restoration techniques are often used. In this paper, a new image restoration way was obtained for blind image. Firstly, the Point Spread Function （PSF） of blurred image was estimated by cepstrum. Secondly, the blurred image was restored by the improved Kalman filter. The cepstrum was the way that the PSF of blurred image could be obtained through analyzing the relationship between two parts. One reflected original image, and the other reflected blurred system. The improved Kalman filter took account of the model error of system during the process of estimation. Some digital simulation experiments were done through Matlab. The results using the improved Kalman filter algorithm based on estimated PSF indicate that the proposed method effectively eliminates the impact caused by inaccurate PSF and it has better effects than Kalman filter.