The spatio-temporal coherence function (STCF) associated with the wavefield from a scene conveys all information required to produce an image of that scene. Through the use of dynamic coding/decoding masks a STCF can be converted in form so as to allow the image-forming information to be conveyed via a single optical fiber to a remote viewing site. A general theory relating to STCF transfer is presented, and a Young's fringe-based discussion of why the scheme is plausible is presented.
The scope of this work is the compensation of the chromatic dispersion inherent to free-space light propagation, both in the Fraunhofer and in the Fresnel diffraction region. The cornerstone of our procedure lies in achieving, in a first-order approximation, the incoherent superposition of the monochromatic versions of the selected diffraction pattern in a single plane and with the same scale for all the wavelengths of the incident light. Our novel optical configurations with achromatic properties for the field diffracted by a screen are formed by a proper combination of a small number of conventional diffractive and refractive lenses, providing an achromatic real image of the diffraction pattern of interest. The residual chromatic aberrations in every case are low even when the spectrum of the incident light spreads over the whole visible region. The resulting achromatic hybrid (diffractive- refractive) systems are applied, in a second stage, for implementing several achromatic diffraction-based applications with white light, like wavelength-independent spatial-frequency filtering, achromatic pattern recognition, white-light array generation, and to designing a totally-incoherent optical processor that is able to perform color processing operations under natural illumination (both spatially and temporally incoherent).
Optical information processing, traditionally employed in the spatial domain, has been experiencing a renaissance with femtosecond laser pulse technology. Temporal optical information can now be manipulated via linear and nonlinear processes, and stored and retrieved, by converting optical signals between the spatial and temporal domains. In this manuscript, we review the state-of-the-art in the spatio-temporal optical signal processing techniques for information data coding, data conversion, signal recording, as well as signal characterization. Applications of these techniques for future computing, communication, storage, and signal processing systems are discussed.
The inclusion of optoelectronic displays has enabled optical correlators to improve radically and maintain the competitive edge of optical processors among information processing fields. In this work, an optical correlator has been implemented by using two VGA liquid crystal displays as spatial light modulators, both at the input and Fourier planes. These devices have been removed from a commercial videoprojector and have been characterized in order to operate in different configurations. This characterization is based on an interferometric procedure which includes amplitude and phase modulation measurements. For a phase-only modulation we have compared the use of linearly and elliptically polarized light. In this latter case we have found an operating curve with phase-only modulation which takes values from 0 to π radians. This is a limitation when a pure phase filter is required as in data security and encryption, in wavelet-based systems, and in optical pattern recognition, among others. An application in this latter field is presented in our work as a solution to overcome this limited phase depth. We propose a modification of the classical phase-only filter based on the use of the absolute value of the phase. Experimental correlation results using the optical setup and the modified filter have been obtained.
Liquid-crystal televisions are inexpensive display devices that can be used as arbitrary quasi-phase modulators to achieve arbitrary wavefront shapes, these are limited only by the available modulation depth and resolution. We discuss the properties of these devices and then demonstrate four applications of a particular liquid-crystal television: an active lens system, programmable optical image processing experiments, the resolution enhancement of an image sensor, and the measurement of the sensitivity of heterodyne detection to wavefront aberrations.
Morphological and rank-order filtering can be performed by combining linear operations and thresholding. In this review we present several approaches for the optoelectronic implementation of these operations. The systems based on this architectures are able to deal with realistic size images at high frame rates. Additionally, the same concepts are applied to nonlinear correlators based on thresholding and linear correlation. The main features, owing to the nonlinearity of the process, are the higher discrimination and the selectivity to target intensity, with independence of the global image intensity.
Many implementations of computer generated holograms (CGH’s) or diffractive optical elements (DOE’s) onto spatial light modulators (SLM’s) have already been considered. In this paper, we first review the various types of SLM’s available for DOE’s and the implementations of DOE’s onto SLM’s already reported in the literature. Then we investigate the point in displaying DOE’s onto SLM’s that couple phase and amplitude modulations, such as twisted nematic-liquid crystal displays (TN-LCD's): we provide computer simulations as well as experimental results.
We present several approaches for visible and infrared video image sequence registration, useful for image fusion, target detection and recognition. Feature inconsistency and low contract and noise in the infrared image background consist of the principle difficulty in the image registration for the well separated spectral bands visible and IR images. Possibility of using and integrating the optical correlator into the operational systems is discussed.
I espouse an approach to optimizing filters on arbitrary SLMs that is different from some approaches to be found in the current literature. The method begins with selecting a metric by which to judge the operation of the correlator. The metric is to be based on observable features, not on inaccessible internal states of the correlator. That metric is optimized by choice of the implemented filter — significantly, the optimization is done under restriction to realizable filter values, not under other restrictions such as to unit filter energy or matching phase inappropriately. A necessary condition of optimality is that the partial derivative of the metric with respect to allowed changes in the realizable filter value is zero. The ramifications of these precepts are examined and examples are shown.
A family of linear and nonlinear processors (filters) for image recognition, which are extensions of the previously developed filters called lp-norm optimum filters, are presented. These filters are lp-norm optimal in terms of tolerance to input noise and discrimination capabilities. The lp-norm is the generalization of the usual mean squared (l2) norm, obtained by replacing the exponent 2 by any positive constant p (usually p ≥ 1). These processors are developed by minimizing the lp-norm of the filter output due to the input scene and the output due to input noise. The minimization is carried out by constraining a function of the filter output to attain a fixed peak value when the input is the target to be detected.
The use of lp-norm to measure the size of the filter output due to noise gives a greater freedom in adjusting the noise robustness and discrimination capabilities. The flexibility in allowing more general type of constraints allows for experimenting and may lead to designing of filters to obtain better performance by selecting an appropriate filter constraint equation to match the metric used to measure the performance of the filter.
we give an unified theoretical basis for developing these filters. This family of filters include some of the existing linear and nonlinear filters.
Recently new approaches for location and/or segmentation of objects with unknown gray levels embedded in non-overlapping noise have been proposed. These techniques are based on the Statistically Independent Region (SIR) model and are optimal in the maximum likelihood sense. In this paper, we review their theoretical bases and propose a unified approach which enlarges their field of application.
Reconfigurable processors bring a new computational paradigm where the processor modifies its structure to suit a given application, rather than having to modify the application to fit the device. The Optically Programmable Gate Array, an enhanced version of a conventional FPGA, utilizes a holographic memory accessed by an array of VCSELs to program its logic. Combining spatial and shift multipexing to store the configuration pages in the memory, the OPGA module is very compact and has extremely short configuration time allowing for dynamic reconfiguration. The reconfiguration capability of the OPGA can be applied to solve more efficiently problems in pattern recognition and digit classification.
The propagation angle 9 between the symmetry axis of a fiber and the principle propagation direction of a beam is conserved over short distances within a step-index multimode fiber. This conservation behavior can be used for multiplexed transmission by assigning different channels to different propagation angles. Furthermore, due to the reduction of the angular spread in the fiber, the temporal bandwidth is increased compared to multi-mode transmission. To realize this angular coding, suitable optical setups for multiplexing and demultiplexing operations were designed. The experimental results on the transmission capabilities of an angular multiplexed multimode fiber are presented.