Robust Depth Estimation and Image Fusion Based on Optimal Area Selection

Sensors

Ik-Hyun Lee²  Muhammad Tariq Mahmood¹ 

[1] School of Computer Science and Engineering, Korea University of Technology and Education, 1600 Chungjeolno, Byeogchunmyun, Cheonan, Chungnam 330-708, Korea; E-Mail:;School of Mechatronics, Gwangju Institute of Science and Technology (GIST), 123 Cheomdan gwagiro, Buk-Gu, Gwangju 500-712, Korea; E-Mail:

关键词: depth estimation;    optimal area selection;    3D camera;   

DOI  :  10.3390/s130911636

来源: mdpi

【 摘 要 】

Mostly, 3D cameras having depth sensing capabilities employ active depth estimation techniques, such as stereo, the triangulation method or time-of-flight. However, these methods are expensive. The cost can be reduced by applying optical passive methods, as they are inexpensive and efficient. In this paper, we suggest the use of one of the passive optical methods named shape from focus (SFF) for 3D cameras. In the proposed scheme, first, an adaptive window is computed through an iterative process using a criterion. Then, the window is divided into four regions. In the next step, the best focused area among the four regions is selected based on variation in the data. The effectiveness of the proposed scheme is validated using image sequences of synthetic and real objects. Comparative analysis based on statistical metrics correlation, mean square error (MSE), universal image quality index (UIQI) and structural similarity (SSIM) shows the effectiveness of the proposed scheme.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.