TY - GEN
T1 - Recursive intelligent matching pursuit method for image sequences reconstruction based on l0 minimization
AU - Li, Dan
AU - Liu, Chaoran
AU - Liu, Xuan
AU - Wu, Zhaojun
AU - Wang, Qiang
AU - Shen, Yi
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/5
Y1 - 2017/7/5
N2 - This paper addresses the image sequences reconstruction by l0 minimization, which is an NP-hard problem with high computational complexity. To solve it, we propose a novel recursive intelligent matching pursuit(RIMP) algorithm in this paper. The idea of RIMP lies in utilizing the recursive reconstruction to reduce the sparsity and applying the superiorities of intelligent optimization algorithm to solve the l0 minimization essentially, which is beneficial to improving the reconstruction accuracy. To reduce the computational complexity, some matching strategies of greedy algorithm are used to design the intelligent searching strategies to accelerate the reconstruction speed. Also, based on the high reconstruction accuracy of the intelligent searching, RIMP can significantly improve the reconstruction accumulation in recursive reconstruction for image sequences. Numerical simulations on several image sequences have been used to demonstrate that the theoretical reconstruction performance of RIMP can be achieved.
AB - This paper addresses the image sequences reconstruction by l0 minimization, which is an NP-hard problem with high computational complexity. To solve it, we propose a novel recursive intelligent matching pursuit(RIMP) algorithm in this paper. The idea of RIMP lies in utilizing the recursive reconstruction to reduce the sparsity and applying the superiorities of intelligent optimization algorithm to solve the l0 minimization essentially, which is beneficial to improving the reconstruction accuracy. To reduce the computational complexity, some matching strategies of greedy algorithm are used to design the intelligent searching strategies to accelerate the reconstruction speed. Also, based on the high reconstruction accuracy of the intelligent searching, RIMP can significantly improve the reconstruction accumulation in recursive reconstruction for image sequences. Numerical simulations on several image sequences have been used to demonstrate that the theoretical reconstruction performance of RIMP can be achieved.
UR - https://www.scopus.com/pages/publications/85026731730
U2 - 10.1109/I2MTC.2017.7969702
DO - 10.1109/I2MTC.2017.7969702
M3 - 会议稿件
AN - SCOPUS:85026731730
T3 - I2MTC 2017 - 2017 IEEE International Instrumentation and Measurement Technology Conference, Proceedings
BT - I2MTC 2017 - 2017 IEEE International Instrumentation and Measurement Technology Conference, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2017
Y2 - 22 May 2017 through 25 May 2017
ER -