In the past, the use of optical and digital three-dimensional correlation methods have been demonstrated to extract velocity data from the complex amplitude distribution of particle images in holographic particle image velocimetry (HPIV). Recently we have proposed a digital shearing method to extract three-component particle displacement data throughout a complete image field. In contrast to full three-dimensional correlation, it has been shown that all three components of particle image displacement can be retrieved using just four two-dimensional fast Fourier transform (FFT) operations and appropriate coordinate transformations. In this paper we describe three-dimensional correlation and digital shearing methods and compare their performance in terms of computational efficiency and measurement accuracy. The simulated results show that the digital shearing method has comparable accuracy to three-dimensional correlation but is significantly faster.
A new simplified Holographic Particle Image Velocimetry technique to make simultaneous measurements of 3D velocity vector information throughout a complex fluid flow is presented in this paper. The method uses a variation of Optical Conjugate Reconstruction with complex correlation analysis and dispenses with the need to have a Holographic Optical Element to correct for distortions introduced by non-uniform windows. Subsequent analysis to extract a map of particle velocity is performed digitally using ray tracing techniques to model the effect of the windows. Results are presented for measurements made within a thick windowed diesel engine, showing that flow velocity vectors can be measured to an accuracy of 3% using the technique and, illustrating the ray trace mapping procedure.
The rapid classification and discrimination of images using spatial distribution of spectral information has widespread applications from remote monitoring of vegetation and pollution damage, to military surveillance and anti-stealth warfare. This paper describes the construction of a practical optical correlator capable of spatial and spectral pattern recognition. The method used here exploits the ability of optical correlators to process information in parallel with high space bandwidth product. For reasons of light efficiency and practical convenience, the spectral information is input into the correlator as a spatial array of coherence or 'white light' fringe patterns. This technique we have called coherence transform imaging (CTI). This paper discusses the relative merits of several interferometric methods to perform CTI including Michelson, Sagnac and Polarizing interferometers. A robust CTI camera utilizing a polarizing interferometer is then described and simple matched filtering operations are performed using CTI images recorded on photographic film. Finally an optical correlator capable of real time spectral discrimination and tracking of colored objects is demonstrated.
KEYWORDS: Optical components, Image processing, Image filtering, Convolution, 3D image processing, Optical filters, Linear filtering, Cameras, Imaging systems, Chemical elements
This paper describes a method to modify the point spread characteristics of an imaging system to perform convolution filtering of incoherent image fields prior to detection. The technique utilizes an aperture plane phase only optical element (kinoform) which is computer generated to optimize efficiency and is fabricated as a bleached hologram. In addition to providing a high speed alternative to digital enhancement of images, optical processing using this approach has several interesting properties. The most significant of these is the ability of the phase element to retain and process high spatial frequency image information from parts of the image which would otherwise be out of focus. As a result this technique allows an optical implementation of three- dimensional convolution filtering, a practical demonstration of which is given in this paper.
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