Document Type

Article

Publication Date

12-1997

Publication Source

IEEE Transactions on Image Processing

Abstract

n many imaging systems, the detector array is not sufficiently dense to adequately sample the scene with the desired field of view. This is particularly true for many infrared focal plane arrays. Thus, the resulting images may be severely aliased. This paper examines a technique for estimating a high-resolution image, with reduced aliasing, from a sequence of undersampled frames. Several approaches to this problem have been investigated previously. However, in this paper a maximum a posteriori (MAP) framework for jointly estimating image registration parameters and the high-resolution image is presented. Several previous approaches have relied on knowing the registration parameters a priori or have utilized registration techniques not specifically designed to treat severely aliased images. In the proposed method, the registration parameters are iteratively updated along with the high-resolution image in a cyclic coordinate-descent optimization procedure. Experimental results are provided to illustrate the performance of the proposed MAP algorithm using both visible and infrared images. Quantitative error analysis is provided and several images are shown for subjective evaluation.

Inclusive pages

1621 - 1633

ISBN/ISSN

1057-7149

Document Version

Postprint

Comments

The document available for download is the authors' accepted manuscript, provided in compliance with publisher policies on self-archiving and with author permission. Some differences may be present during the editing and layout processes. Permission documentation is on file.

Publisher

Institute of Electrical and Electronics Engineers

Volume

6

Issue

12

Peer Reviewed

yes

Keywords

antialiasing, error analysis, focal planes, image registration, image resolution, image sampling, image sequences, infrared imaging, maximum likelihood estimation, optimisation, MAP registration, aliased images, cyclic coordinate-descent optimization, detector array, error analysis, experimental results, gradient descent optimization, high-resolution image estimation, image registration parameters, imaging systems, infrared focal plane arrays, maximum a posteriori estimation, performance, reduced aliasing, registration parameters, subjective evaluation, undersampled image sequence, visible images, Detectors, High-resolution imaging, Image registration, Infrared imaging, Iterative algorithms, Layout, Optical imaging, Optimization methods, Parameter estimation, Sensor arrays