POCS-embedded MAP method for image super-resolution restoration

Author

Wei, Baoguo ; Hui, Weihua

Author_Institution

Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´´an

fYear

2009

fDate

25-27 May 2009

Firstpage

3791

Lastpage

3794

Abstract

Super-resolution image restoration produces a high-resolution image from a set of shifted, blurred, and decimated versions thereof. The quality of super-resolution depends on the accuracy and the amount of a priori information that could be utilized in the processing. In this paper, a POCS-embedded MAP based super-resolution image restoration algorithm is proposed, which incorporates POCS constraints and MAP algorithm. Experiments demonstrate that POCS-embedded MAP algorithm can achieve a better restoration result than traditional MAP and POCS approach.

Keywords

image resolution; image restoration; maximum likelihood estimation; optimisation; POCS-embedded MAP method; image super-resolution restoration algorithm; projection onto convex set theory; statistical optimization; Additive white noise; Bayesian methods; High-resolution imaging; Humans; Image processing; Image resolution; Image restoration; Inverse problems; Layout; Optimization methods; Image processing; Image restoration; MAP; POCS; Superresolution;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on

Conference_Location

Xi´an

Print_ISBN

978-1-4244-2799-4

Electronic_ISBN

978-1-4244-2800-7

Type

conf

DOI

10.1109/ICIEA.2009.5138914

Filename

5138914