The image super resolution reconstruction based on wavelet decomposition and Markov random field

Hongjiu Tao; Keming Jia; Xiaojun Tong

doi:10.1117/12.573863

8 February 2005 The image super-resolution reconstruction based on wavelet decomposition and Markov random field

Hongjiu Tao, Keming Jia, Xiaojun Tong

Proceedings Volume 5637, Electronic Imaging and Multimedia Technology IV; (2005) https://doi.org/10.1117/12.573863
Event: Photonics Asia, 2004, Beijing, China

Abstract

Taking into account the lack of prior-information on account of single image, we design a image super-resolution reconstruction method, based on the possibility and the theory basis of the single image super-resolution reconstruction. Analysis of the process of the algorithm is also included. Because the theory and method of Markov random field are being developed constantly, the theory and method may described the part statistic of the image. The paper analyses the image super resolution reconstruction based on Markov Random Field, this apply the image super resolution processing. This presented a super resolution reconstruction technique based on wavelet decomposition and Markov Random Field, and has carried on the experimental research. Experiment result proves that the super resolution processing method on the basis of the Markov random field (MRF) can obtain the good super resolution restoration processing result.

Citation Download Citation

Hongjiu Tao, Keming Jia, and Xiaojun Tong "The image super-resolution reconstruction based on wavelet decomposition and Markov random field", Proc. SPIE 5637, Electronic Imaging and Multimedia Technology IV, (8 February 2005); https://doi.org/10.1117/12.573863

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