Abstract
Phase unwrapping is a fundamental problem in Time-of-Flight (ToF) imaging, especially when high modulation frequency is used to achieve precise measurement accuracy. This paper proposes a novel double-frequency based phase unwrapping method for ToF sensors. The new method incorporates the idea of image segmentation to solve phase unwrapping region-by-region instead of pixel-by-pixel. The depth image is segmented based on the constraint between depth measurements and wrap numbers at two modulation frequencies. To avoid misclassification of the pixels around phase jump edges in the presence of inevitable noise, we employ a modified distance function to classify the edge pixels into the corresponding connected area. Furthermore, a graph model is used to accurately model the phase jumping relation between different connected areas. On this basis, we propose an MRF framework to fuse the amplitude and depth information to unwrap the phase. Experimental results on both synthetic and real-world data demonstrate that, the proposed method is robust to noise and outperforms state-of-the-art methods, while being highly efficient enabling real-time running.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.