Performance comparison of a linear parametric noise estimation Wiener filter and non-linear joint transform correlator for realistic clutter backgrounds

• Published in: Optics communications 2000-08, Vol.182 (1), p.83-90
• Main Authors: Tan, Sovira, Young, Rupert C.D, Budgett, David M, Richardson, John D, Chatwin, Chris R
• Format: Article
• Language: English
• Subjects: Clutter noise suppression; Computers in experimental physics; Exact sciences and technology; Fundamental areas of phenomenology (including applications); Image processing; Imaging and optical processing; Instruments, apparatus, components and techniques common to several branches of physics and astronomy; Non-linear joint transform correlator; Optical correlators; Optical elements, devices, and systems; Optical processors, correlators, and modulators; Optics; Pattern recognition; Physics; Wiener filter
• ISSN: 0030-4018; 1873-0310
• DOI: 10.1016/S0030-4018(00)00796-3

It has been shown previously that a linear Wiener filter is capable of detecting a target in severe clutter backgrounds by utilising a parametric model of the clutter power spectrum in its filter transfer function. In this paper the performance of the linear Wiener filter is compared to that implemented in a non-linear joint transform correlator in which the entire current input scene is used as an approximation for the clutter background. Realistic clutter backgrounds are employed in the tests that cover a range of natural scenery likely to be encountered in practice. The linear Wiener filter, employing a parametric model of the averaged background scenes, is shown to outperform the non-linear filter in most cases. Brief consideration is also given to the relative merits of implementation of these two filters in both optical and digital correlators.