基于全向总变分最小化的折反射散焦模糊图像复原方法

Image Restoration for Catadioptric Defocus Blur Based on Omni-Total Variation Minimization

针对折反射全向成像特点,提出了基于全向总变分最小化的折反射散焦模糊图像复原方法。随着高分辨率图像传感器器件和大光圈镜头的采用,光圈和反射面曲率造成的折反射全向成像散焦模糊问题越发突出。由于在折反射全向图像上,具有相邻位置关系的两个点,在真实世界中并不具有相同的依赖关系,因此传统的图像梯度计算方法并不适合折反射全向图像处理。提出结合全向图像成像特点的全向梯度计算方法,将全向总变分最小化作为正则化条件,对散焦模糊全向图像进行复原,得到全局清晰的全向图像。

Combined with the characteristics of catadioptric omnidirectional imaging, the method of image restoration for catadioptric defocus blur based on omni-total variation minimization is proposed. The problem of catadioptric omnidirectional imaging defocus blur, which is caused by lens aperture and mirror curvature, becomes more severe when high resolution sensors and large apertures are applied. In the catadioptric omnidirectional image, the two points near each other do not have the relation in true scene. So the traditional gradient computation cannot fit catadioptric omnidirectional image processing. The omni-gradient computing method combined with the characteristics of omnidirectional imaging is proposed. Then, the omni-total variation minimization is used as the condition of deconvolution regularization, which is used for the defocus blur omnidirectional image restoration to obtain all sharp omnidirectional images.