Cheong Hejin, Chae Eunjung, Lee Eunsung, Jo Gwanghyun, Paik Joonki
Department of Image, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 156-756, Korea.
Sensors (Basel). 2015 Jan 6;15(1):880-98. doi: 10.3390/s150100880.
This paper presents a fast adaptive image restoration method for removing spatially varying out-of-focus blur of a general imaging sensor. After estimating the parameters of space-variant point-spread-function (PSF) using the derivative in each uniformly blurred region, the proposed method performs spatially adaptive image restoration by selecting the optimal restoration filter according to the estimated blur parameters. Each restoration filter is implemented in the form of a combination of multiple FIR filters, which guarantees the fast image restoration without the need of iterative or recursive processing. Experimental results show that the proposed method outperforms existing space-invariant restoration methods in the sense of both objective and subjective performance measures. The proposed algorithm can be employed to a wide area of image restoration applications, such as mobile imaging devices, robot vision, and satellite image processing.
本文提出了一种快速自适应图像恢复方法，用于去除普通成像传感器中空间变化的离焦模糊。在使用每个均匀模糊区域中的导数估计空间可变点扩散函数（PSF）的参数之后，该方法通过根据估计的模糊参数选择最佳恢复滤波器来执行空间自适应图像恢复。每个恢复滤波器以多个FIR滤波器的组合形式实现，这保证了无需迭代或递归处理即可快速进行图像恢复。实验结果表明，该方法在客观和主观性能指标方面均优于现有的空间不变恢复方法。所提出的算法可应用于广泛的图像恢复应用领域，如移动成像设备、机器人视觉和卫星图像处理。
