基于联合双边滤波的深度图像增强算法

Depth Image Enhancement Algorithm Based on Joint Bilateral Filtering

主动光设备是目前获取深度图的主要方法,被广泛应用于导航、人机交互、增强现实等领域。但主动光设备存在分辨率低、空洞、边缘不匹配等问题。为此,提出一种基于联合双边滤波的深度图像增强算法。采用基于深度的前景分割方法,找出深度图与彩色图边缘不匹配像素集合,利用基于联合双边滤波的插值算法对空洞进行填充。为更好保持边缘细节,增加引导深度相似项与梯度域项的方法进行插值。实验结果表明,该算法比已有方法的最小均方误差平均减少约13%,具有更好的保持边缘效果。

Depth image captured by active sensor is a current tendency, which is widely used in navigation, human computer interaction, augmented reality and so on. However, common low-cost sensors have their own disadvantages, such as low resolution, holes, unmatched boundary of edge. For these problems, this paper proposes a depth image enhancement algorithm based on improved joint bilateral filtering. Depth-based foreground segmentation method is adopted to figure out the set of pixels of unmatched foreground edge, and interpolation algorithm based on joint bilateral filter is used to fill the holes. Meanwhile, in order to make further improvement, guided depth similar item and gradient item are introduced to preserve edge structure. Experimental results show that compared with the existing joint bilateral interpolation, the improved method decreases the Mean Squared Error（MSE） by 13% in average which has better effect on edge-preserving.