TY - GEN
T1 - Depth image super-resolution using internal and external information
AU - Zheng, H.
AU - Bouzerdoum, A.
AU - Phung, S. L.
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/8/4
Y1 - 2015/8/4
N2 - The fast development of 3-D imaging techniques has increased demands for high-resolution depth images. Conventional depth super-resolution methods reconstruct the high-resolution image by accessing high frequency information, either internally from a high-resolution intensity image or externally from a high-resolution image database. In this paper, a new depth super-resolution method based on joint regularization is proposed, which exploits both internal and external high frequency information. Specifically, a joint regularization problem with different constraints is formulated, which allows us to solve for the high-resolution image and a sparse code simultaneously. These constraints are constructed by utilizing information from both internal and external high-frequency sources. Experimental evaluation suggests that the proposed method provides improved results over existing approaches, in terms of both visual appearance and objective image quality.
AB - The fast development of 3-D imaging techniques has increased demands for high-resolution depth images. Conventional depth super-resolution methods reconstruct the high-resolution image by accessing high frequency information, either internally from a high-resolution intensity image or externally from a high-resolution image database. In this paper, a new depth super-resolution method based on joint regularization is proposed, which exploits both internal and external high frequency information. Specifically, a joint regularization problem with different constraints is formulated, which allows us to solve for the high-resolution image and a sparse code simultaneously. These constraints are constructed by utilizing information from both internal and external high-frequency sources. Experimental evaluation suggests that the proposed method provides improved results over existing approaches, in terms of both visual appearance and objective image quality.
KW - depth super-resolution
KW - joint regularization
KW - local constraint
KW - non-local constraint
KW - sparse representation
UR - http://www.scopus.com/inward/record.url?scp=84946015033&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2015.7178161
DO - 10.1109/ICASSP.2015.7178161
M3 - Conference contribution
AN - SCOPUS:84946015033
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 1206
EP - 1210
BT - 2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015
Y2 - 19 April 2014 through 24 April 2014
ER -