Aliasing as noise: a quantitative and qualitative assessment

Stephen K. Park; Rajeeb Hazra

doi:10.1117/12.154738

31 August 1993 Aliasing as noise: a quantitative and qualitative assessment

Stephen K. Park, Rajeeb Hazra

Proceedings Volume 1969, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing IV; (1993) https://doi.org/10.1117/12.154738
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

Natural scenes are not band-limited and for most contemporary sampled imaging systems, the (pre-sampling) image formation subsystem frequency response extends well beyond the sampling passband. For these two reasons, most sampled imaging systems -- particularly staring-array systems -- produce aliasing. That is, the sampling process causes (high) spatial frequencies beyond the sampling passband to fold into (lower) spatial frequencies within the sampling passband. When the aliased, sampled image data is then reconstructed, usually by image display, potentially significant image degradation can be produced. This is a well- established theoretical result which can be (and has been, by many) verified experimentally. In this paper we argue that, for the purposes of system design and digital image processing, aliasing should be treated as signal-dependent, additive noise. The argument is both theoretical and experimental. That is, we present a model-based justification for this argument. We demonstrate that our model-based argument leads naturally to system design metrics which quantify the extent of aliasing. And, by illustrating several `aliased component' images, we provide a qualitative assessment of aliasing as noise.

Citation Download Citation

Stephen K. Park and Rajeeb Hazra "Aliasing as noise: a quantitative and qualitative assessment", Proc. SPIE 1969, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing IV, (31 August 1993); https://doi.org/10.1117/12.154738

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