场景深度无关的虚拟孔径图像鬼影去除算法

Depth Free Ghost Artifacts Reduction on Synthetic Aperture Imaging

与传统成像系统相比,虚拟孔径成像的深度分辨率大为提高,但虚拟孔径图像的散焦区域普遍存在较严重的鬼影问题。提出一种基于熵值计算的鬼影去除算法,特点在于无须进行场景深度估计。首先,依据光场理论分析了鬼影产生原因;随后,提出了预测图像点聚焦趋势的假设,并依此逐像素计算熵值估计低通滤波器的核函数;根据相邻像素点相似性和相邻聚焦深度图像连续性,采用在空域低通滤波的方法实现图像鬼影去除。在仿真数据和真实数据的实验表明,该算法能够有效去除鬼影,并能保持虚拟孔径图像聚焦区域的清晰成像,从而验证了文中所提出算法的有效性。

Compared to traditional imaging system, the depth resolution is significantly improved in the synthetic aperture photography （SAP） system. However, the ghost artifact is brought into defocused regions of SAP images, and that is an unexpected side effect in most applications. In this paper, we propose an entropy based ghost removal algorithm on SAP images. Our algorithm is free of depth estimation, which is still an open problem in computer vision. We first characterize the essence of ghost artifact by light field theory. Then, we detect the focus trend by introducing entropy based assumptions. We finally employ a ghosting, in which the assumptions are used for estimating ting artifacts is greatly smoothed by applying the proposed are preserved in the focused region. spatial domain low pass filter to reduce the unexpected the kernel function. Experimental results show that ghosalgorithm. In the mean time, the sharp focused regions are preserved in the focused region.