Depth Map Super-Resolution Based on the Local Structural Features of Color Image
YANG Yu-Xiang1,WANG Zeng-Fu1,2
1. Department of Automation,University of Science and Technology of China,Hefei 230026 2. Institute of Intelligent Machines,Chinese Academy of Sciences,Hefei 230031
Abstract:It is convenient for time of flight camera to get the scene depth image,the resolution of depth image is very low due to limitations of the hardware,which can not meet the actual needs. In this paper,a method is proposed for solving depth map super-resolution problem. With a low resolution depth image as input,a high resolution depth map is recovered by using a registered and potentially high resolution camera image of the same scene. The depth map super-resolution problem is solved by developing an optimization framework. Specifically,the reconstruction constraint is applied to get the data term,and based on the fact that discontinuities in range and coloring tend to co-align,laplacian matrix and local structural features of high resolution camera images are used to construct the regularization term. The experimental results demonstrate that the proposed approach gets high resolution range image in terms of both its spatial resolution and depth precision.
杨宇翔,汪增福. 基于彩色图像局部结构特征的深度图超分辨率算法[J]. 模式识别与人工智能, 2013, 26(5): 454-459.
YANG Yu-Xiang,WANG Zeng-Fu. Depth Map Super-Resolution Based on the Local Structural Features of Color Image. , 2013, 26(5): 454-459.
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