Abstract
Integral imaging is a kind of 3D display with no glasses, which represents the future developments. Elementary image array (EIA) is an essential component of integral imaging. Our coding framework includes pre-processing, modeling, and reconstruction. We acquire the sub-EIA from the original EIA and get the offsets between adjacent elementary images (EIs) through pre-processing. As for modeling, we get the optimal combination of 3-D Epanechnikov Mixture Regression (3-D EMR) or 3-D Gaussian Mixture Regression (3-D GMR) by Elementary Image Adaptive Model Selection (EI-AMLS) algorithm to achieve the best modeling of sub-EIA. Finally, the linear-based reconstruction is completed according to the correlation between adjacent EIs. Our decoded images realize a clearer outline reconstruction and more superior coding efficiency than HEVC and JPEG2000 below about 0.05bpp. Furthermore, the proposed method can achieve the same visual effect as HEVC with only 15% to 80% time consumed.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Visual Communication and Image Representation
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.
