Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Digital interferometry for flow visualization in the presence of gross periodic noise

Open Access Open Access

Abstract

Digital interferometry is a hybrid optical-digital two-exposure holographic technique in which the interferogram image intensity is recorded at each of several, known, discrete phase shifts. From these image data the sign and magnitude of the interferogram phase may be evaluated to a high degree of accuracy. This technique is especially useful in flow visualization because it allows visu­alization of very weak flows and aids in understanding very complex ones. In nonreal-time digital interferometry, two references are used. Reconstruction with both references creates a high contrast fringe pattern on the hologram surface. Although this may be minimized by imaging techniques, it severely degrades the interferogram in applications requiring the object to be close to the hologram. This noise causes periodic distortion of the computed phase, in some cases completely washing out the signal. However, applying image filtering algorithms to the image data can remove the noise from heavily degraded images and allow the signal to be faithfully reconstructed. We dis cuss image filtering methods and present several experimental examples including the use of this technique with pulsed laser interferometry.

© 1986 Optical Society of America

PDF Article
More Like This
Flow-field visualization by holographic interferometery in iron-doped lithium niobate crystals

J. H. Mitchell, R. Magnusson, T. D. Black, and D. R. Wilson
MW3 OSA Annual Meeting (FIO) 1986

Sub-Nyquist Interferometry

J. E. Greivenkamp
PD2 Optical Fabrication and Testing (OF&T) 1986

Holographic Interferometry with Fringe Control and On-Line Digital Phase Measurement

Maurice Halioua and Toni Sue Bowins
MA4 Holography (Holography) 1986

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.