Reconstruction algorithm of infrared video image based on compressed sensing

Qing Xu; Lijun Yun; Junsheng Shi

doi:10.1117/12.946580

2 June 2012 Reconstruction algorithm of infrared video image based on compressed sensing

Qing Xu, Lijun Yun, Junsheng Shi

Proceedings Volume 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012); 833418 (2012) https://doi.org/10.1117/12.946580
Event: Fourth International Conference on Digital Image Processing (ICDIP 2012), 2012, Kuala Lumpur, Malaysia

Abstract

Compressed sensing is a novel signal sampling theory emerging recently. It is a theory that signals could be sampled far below the Nyquist sampling rate. This paper introduces compressed sensing theory into the application of infrared video, proposes a new residual reconstruction algorithm, and establishes a new infrared video codec model with random Gaussian matrix as the measurement matrix and with orthogonal matching pursuit algorithm as the reconstruction method. On the platform of Matlab, this paper performs the reconstruction of infrared video frames. The simulation results verify that the proposed algorithm can provide a good visual quality and speed up evidently by comparison with conventional algorithm.

Citation Download Citation

Qing Xu, Lijun Yun, and Junsheng Shi "Reconstruction algorithm of infrared video image based on compressed sensing", Proc. SPIE 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012), 833418 (2 June 2012); https://doi.org/10.1117/12.946580

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available