Variational Bayesian super resolution acceleration using preconditioned conjugate gradient

Jingyu Chen M.D.; Yigang Wang; Shi Li

doi:10.1117/12.2502870

9 August 2018 Variational Bayesian super resolution acceleration using preconditioned conjugate gradient

Jingyu Chen M.D., Yigang Wang, Shi Li

Proceedings Volume 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018); 108066O (2018) https://doi.org/10.1117/12.2502870
Event: Tenth International Conference on Digital Image Processing (ICDIP 2018), 2018, Shanghai, China

Abstract

The high computational complex of Super Resolution (SR) is a focused topic in many imaging applications, which involves to solve huge sparse linear systems. Solving such systems usually employs the iterative methods, such as Conjugate Gradient (CG). But in most variational Bayesian SR algorithms, CG method converges slowly with the coefficient matrix being ill-conditioned and takes long execution time. In this paper, we propose Preconditioned Conjugate Gradient (PCG) to solve the problem and analyze the performance of the different PCG solvers, Jacobi and incomplete Cholesky decomposition(IC). Experimental results demonstrate that the new method achieves accelerations compared with the traditional one while maintaining high visual quality of the reconstructed HR image, and, especially, the IC solver has a better performance.

Citation Download Citation

Jingyu Chen M.D., Yigang Wang, and Shi Li "Variational Bayesian super resolution acceleration using preconditioned conjugate gradient", Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108066O (9 August 2018); https://doi.org/10.1117/12.2502870

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