Share Email Print

Proceedings Paper

Superresolution of blurred infrared images using the blur parameters identification on the neural network
Author(s): Nan Zhang; Weiqi Jin; Binghua Su
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Images acquired from an infrared (IR) sensor typically suffer from poor spatial resolution due to the finite size of the lens that makes up the imaging system and the consequent imposition of the underlying diffraction limits. The lost frequency components beyond the diffraction-limited cutoff make the obtained images blur. Currently there are one kind of image processing schemes referred to as super-resolution algorithms available for solving of this problem, including Bayesian analysis methods, set theoretic methods, and Fourier domain techniques. But an estimate of the blur model parameters is essential in these methods. If incorrect blur parameters are chosen then the super-resolution results will be wrong. This work presents an original solution to the blur parameters identification problem in infrared image super-resolution. A back-propagation(BP) neural network is used for the blur parameters identification. In this method, we consider the modulation transfer function (MTF) of an infrared system as a Gaussian type. Mathematical analysis shows that using back-propagation neural network it is possible to identify the parameters of the Gaussian blur. After blur parameters identification, the image can be restored using several kinds of methods. We choose the Poisson-MAP super-resolution algorithm with Markov constraint(MPMAP) as our restoration method. Experimental results demonstrate that the performance of the MPMAP method using the blur parameters identified by our neural network is superior to other blind image restoration methods.

Paper Details

Date Published: 10 January 2005
PDF: 6 pages
Proc. SPIE 5640, Infrared Components and Their Applications, (10 January 2005); doi: 10.1117/12.573445
Show Author Affiliations
Nan Zhang, Beijing Institute of Technology (China)
Weiqi Jin, Beijing Institute of Technology (China)
Binghua Su, Beijing Institute of Technology (China)

Published in SPIE Proceedings Vol. 5640:
Infrared Components and Their Applications
Haimei Gong; Yi Cai; Jean-Pierre Chatard, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?