This PDF file contains the editorial “Editorial: The Conference I Missed” for OE Vol. 31 Issue 05

This PDF file contains the editorial “Guest Editorial: Optical Information Processing” for OE Vol. 31 Issue 05

We investigate a binary encoding technique to represent grayscale nonlinear joint transform correlators. We show that the joint power spectrum can be binary encoded to represent gray-scale nonlinear joint transform correlators. The threshold function is computed analytically in terms of the power spectra of the input signal and the reference signal. Computer simulations of the correlation tests for various degrees of nonlinear transformation of the joint power spectrum are presented.

A new power spectrum binarization technique is introduced that eases experimental implementation while significantly improving binary joint transform correlation performance. Impacts of fundamental design parameters on correlator performance have been evaluated using computer simulations. Realistic images including multiple objects in challenging backgrounds were used to characterize the effects of parameter variations such as threshold levels and low-frequency blocks. The design aspects emphasized were those contributing to ease of experimental implementations, including practical dynamic range limitations and achievable threshold levels. Experimental results using the optimization techniques developed with simulations are given.

We review the optical system requirements for full-text retrieval operations that utilize optical storage devices and optical pattern-matching techniques. We propose an optoelectronic full-text retrieval system (OPTORETRIEV) that includes a two-dimensional optical pattern matcher containing an optical-disk-based photorefractive joint transform correlator. We then show how this optical pattern matcher is used to perform various full-text search operations. The proposed system is a massively parallel machine taking advantage of optic's inherent parallelism. We also discuss how optics can impact the area of information retrieval. It is estimated thatthe system can perform pattern matching at a rate of over 160 Gbits/s, which is at least several orders of magnitude faster than current electronic systems. However, considerable research and development needs to be performed, especially in optical devices, before such a system could become a reality.

A new synthetic discriminant function (SDF) design approach is presented that yields the best approximation of arbitrary output correlation shapes in the minimum squared error (MSE) sense. We term such filters as MSE-SDFs. Simulation results are presented to illustrate the advantages of MSE-SDFs. Also, we show that MSE-SDFs generalize minimum average correlation energy filters.

In the past, several different approaches to synthetic discriminant function (SDF) filter design have been proposed, including conventional SDFs, which control the correlation values at the origin; minimum variance SDFs (MVSDFs), which minimize the noise sensitivity of the filters; minimum average correlation energy (MACE) filters, which maximize the peak sharpness; and linear phase coefficient composite (LPCC) filters, which are obtained as the sum of training images weighted by linear phase coefficients. We introduce a new family of SDF filters of which all the above are special cases. Each filter in this family is characterized by two parameters α₁ and α₂. Various choices of (α₁ , α₂) lead to the above special filters. For example, α₁ = 1 and α₂ = 0 leads to MACE LPCC filters, which are hybrid versions of MACE and LPCC filters. This family of filters is evaluated using the minimum probability of error (MPE) criterion and a database of aircraft images. These simulation experiments confirm the superior performance of this filter family. Also, we observe the interesting result that the MPE is at its lowest not for one of the four special filters listed above, but for a combination of them.

Experiments on nonlinearly transformed matched filters for optical correlation are provided. Experimental results for the images tested indicate that nonlinear matched filters produce good correlation perlormance in terms of correlation peak intensity, signal-to-noise ratio, and peak-to-sidelobe ratio. The sensitivity of the k'th law nonlinearly transformed filter to rotational changes of the input signal is investigated. It is shown that for the images presented here, up to a certain degree of input signal rotation, a highly nonlinearly transformed matched filter may produce a larger peak-to-sidelobe ratio than a conventional matched filter.

A rotation invariant optical correlator using a low-cost, liquid crystal television (LCTV) in the Fourier plane is described. The performance of the LCTV used as a filter support medium is evaluated, using interferometric measurements and an image reconstruction experiment. Different operating modes of an LCTV suitable for encoding binary phase-only filters are discussed. Finally, a modified LCTV is used in the filter plane of a conventional 4-f correlator to encode unipolar binary phase-only matched filters and unipolar binary phase-only circular harmonic filters. Optical experimental results are compared with the results of computer experiments.

Two optical pattern recognition methods for characterizing spherical and nonspherical aerosols and particulates are presented. The overall objective of size distribution determination in nearly real time under conditions of high particulate loading is specified. A holographic version of the commercially available wedge-ring detector is described to replace the classical matched filter and some of the possible benefits are enumerated. Computer simulations utilizing the classical matched filter and the holographic ring detector and experimental data collected for opaque spherical particles are included.

A hybrid electro-optic image processor has been developed for automatic target recognition and tracking using an acousto-optic correlator and digital electronics. The optical system performs the computationally intensive correlation operation on the large 2-D input scenes. The electronics provide the decision-making capability and also perform part of the postprocessing needed for increasing the peak-to-clutter ratio in cluttered scenes. The system is able to analyze each correlation plane and apply a real-time template selection algorithm to accommodate scale or rotation changes of the target. A demonstration of the current system capabilities is presented using a terrain board with several different types of stationary and moving model vehicles.

The amplitude- and phase-modulating properties of liquid crystal televisions (LCTVs) are becoming increasingly well known. The Epson Crystal Image video projector is a relatively new TV and uses three liquid crystal panels to encode the red, green, and blue components of the video signal onto the projector light. These panels can be removed for use in optical systems. We present the results from measurements of the phase- and amplitude-modulation properties of one of these LCTV panels.

The three optical information processing techniques of detection, recognition, and identification can and should be combined to achieve the best benefits of each. All methods are required for difficult pattern recognition problems. We consider the identification of multiple objects in the field of view in clutter. A morphological correlator is used to achieve detection. Hierarchical and symbolic pattern recognition correlators can also achieve detection as well as recognition. For very large class probems, feature extractors are required for identification, but first require detection. For difficult multiclass discrimination problems, neural net methods (rather than linear discriminant functions) are needed for identification.

An optical quadratic neural network utilizing four-wave mixing in barium titanate (BaTiO₃) has been developed. This network implements a feedback loop using a CCD camera, a microcomputer, two monochrome liquid crystal televisions, and various optical elements. For training, the network employs the supervised quadratic perceptron algorithm to associate binary-valued input vectors with specified training vectors. Using a spatial multiplexing scheme for two bipolar neurons, the quadratic network was able to associate an input vector with various target vectors. In addition, the network successfully associated two input vectors with two corresponding target vectors in the same training session. Both analytical and experimental results are presented.

Neural network models for associative memory are derived independently on the basis of an optimization principle without resort to any assumptions related to biological principles. All the features of the Hopfield model, such as the updating rule with nonlinear threshold, the outer product algorithm, the symmetric and zero-diagonal interconnection matrix, and asynchronous timing, are automatically derived from a simple optimization principle for bipolar and binary variables. The derivation is extended to generate higher order models that have higher storage capacity and better convergence. The computational circuits to implement the neural network models are also derived naturally from the same principle. Various optical implementations of the computational circuits are also described.

Present techniques and new perspectives of microscopic fluorescence spectroscopy in cellular diagnosis are outlined. Recent applications include the detection of mitochondrial respiratory deficiencies and the intracellular location and light-induced reactions of photosensitizing porphyrins.

The fringe visibility in pulsed subtraction and addition TV holography is described and compared. Correlation fringe patterns, obtained by conventional double-pulse addition TV holography, are characterized by their relatively poor quality. The fringe visibility is significantly improved by applying subtraction in combination with the double-pulse technique. This is achieved by using a standard interline transfer CCD camera. Double-pulse subtraction TV holography is especially useful for subfringe measurements, and vibration amplitudes of less than λ/50 have been detected on raw double-pulse subtraction interferograms.

For both the binary and gray scales, mean square optimal digital morphological filters have been characterized previously in terms of the Matheron erosion representation for increasing, translation-invariant mappings. Included in the characterization is the minimal search strategy for the optimal filter basis; however, without prior statistical information or an adequate image-noise model, even in the binary setting, filter design is computationally intractable for moderately sized observation windows. The mitigation of the computational burden via design constraints is the focus here. Although the resulting filter will be suboptimal, if the constraints are imposed in a suitable manner, little loss of filter performance occurs in return for design tractability. Three approaches are considered: limiting the number of terms in the Matheron expansion, constraining the observation window, and employing structuring element libraries. In the latter methodology various sublibraries are formed and a suboptimal filter is derived from image-noise statistics in conjunction with a basis search restricted to relevant sublibraries. This study analyzes two techniques for library construction: the expert approach involves prior sublibrary formation based on knowledge of important filter bases and the first-order approach employs single-erosion statistical information to limit the basis search to likely useful candidates.

A method to merge images from different sensing modalities for visual display was introduced by Toet, van Ruyven, and Valeton in 1989, which produces a fused image by nonlinear recombination of the ratio of low-pass (R0LP) pyramidal decompositions ofthe original images. The appearance of merged images that are produced by this scheme is highly dependent on the contrast and mean gray level ofthe input images. That nonlinear multiplication of the successive layers of a ratio of low-pass pyramid results in a contrast-enhanced image representation that is highly invariant for changes in the global gray-level characteristics of the original image is shown. Application of this nonlinear multiplication procedure in the image fusion process results in composite images that appear highly independent of changes in lighting and gray-level gradients in the input images. The method is tested by merging different degraded versions of parallel registered thermal (FLIR) and visual (CCD) images.

Circular scanning of the image provides an efficient and simple way to achieve feature extraction of 2-D images. The obtained features are insensitive to object's position, orientation, and scale. The main shortcoming of the method is that such features do not uniquely determine the shape of an object. An overview of the method is presented. An experiment with recognition of latin capitals in two different fonts and scales is described and results are given.

Traditional methods of assessing optical quality are based primarily on global parameters such as the rms wavefront error or performance quantifiers such as the optical quality factor (OQF). Global parameters that characterize performance, such as rms, are indirectlycorrelated with imaging quality because they do not account for the spatial distribution of the errors in the aperture. Although the conventional OQF is related to performance for systems affected with arbitrary aberration forms, it does not supply information that is useful for correcting the local regions of an optical component (e.g., mirror surface). A system is presented that is directly correlated with imaging quality. The system, denoted localized wavefront performance analysis (LWPA), evaluates quality on the basis of a subpupil or local OQF (LOQF) that is specific to discrete regions of the aperture. This information is used to produce a performance map, LOQF versus pupil position, to pinpoint for correction those wavefront error regions with the lowest values. LWPA theory is described heuristically and a supporting test case is presented.

The main aerosol effect on imaging performance is brightness reduction through scattering losses. This is fairly well understood and modeled. However, one phenomenon that is almost always overlooked is the blurring of images that can result from forward-scattered radiation, i.e., the radiation reaching the image plane after being scattered by airborne particles. The paper describes a new and efficient method of calculation of the forward-scattering effect on the point spread and modulation transfer functions. Solutions are presented that show the dependence of the aerosol blurring effect on particle concentration, particle size, geometry, and size of object features. The paper also reports on a simple experiment for measuring the visible point spread function through fog and rain. In most cases, the measurements are in good agreement with the model predictions. As it turns out, our measurements performed at ranges of 500 and 900 m and optical depths of up to seven show significant aerosol blurring effects only for rain and for some advection fogs with a sufficient number of particles in the size range of about 100 μm.

Point projection along a path that includes a rotating mirror is considered. As an example, image patterns are specifically calculated for a rectangular aperture projected onto a cylindrical object when viewed through a complementary optical system offset from the projection optics. These patterns are relevant to the operation of a novel tracking colorimeter for use during paper manufacture.

The statistical behavior of ground-based IR cloudy sky images are analyzed to acquire a priori knowledge of the background necessary for the development of sophisticated infrared target detection and recognition systems. Infrared cloudy sky images can be automatically segmented into their related groups of interest, according to the radiance statistical distribution, by implementing specialized image processing techniques. Once the images have been segmented, the cloud cover, statistical distribution, and other parameters of interest are readily obtained. It was found that, in the 8- to 1 2-μm spectral window, cloudy sky images must be divided into at least five regions of interest, and in the 3- to 5-μm spectral window, a distinction must be made between shaded cloud images and sunlit cloud images. Shaded cloud images have only three regions of interest, whereas sunlit cloud images are more complex and have at least five regions of interest. If each region is approximated by a Gaussian distribution, then the normalized cross-correlation function ofthe measured data with the multinormal function gives a value in excess of 0.9.

Infrared zoom lens systems have benefited from advances in the state ofthe art during the past decade. These advances have included extending the zoom range, improvements in performance, reduction of size and weight, and minimizing complexity. The application of these developments to infrared zoom lens design is presented. The zoom lens systems of several companies active in the field are reviewed, with some reference to tolerancing techniques for production. Innovative reflective zoom systems are also considered. Promising future developments are discussed.

The relative performance of solar-pumped Nd:YAG and Nd:Cr:GSGG lasers was evaluated at both 300 and 80 K. Measurements of the slope efficiency and the lasing threshold were made on several lasers containing these crystals. The stress-induced birefringence and the divergence were also studied. The measurements were used to calculate the values of the intrinsic efficiencies and the losses at both temperatures. The possible mechanisms for the observed temperature dependence are discussed. Due to the improved thermal conductivity of the laser crystals at low temperature, all lasers showed significantly improved performance at low temperature. Both the slope efficiencies and the thresholds improved by a factor of 2 to 3 on cooling. The absolute value of the beam quality, and its sensitivity to changes in the resonator configuration or pump power were significantly better at low temperature.

Since laser exposure in humans is usually limited to accident cases, precise definition of its effects on visual function is difficult to come by. To determine more preciselythese effects and atwhat exposure levels they occur, animal models are required. This immediately poses the problem of how to appropriately ask the animal what it can see. Under the assumption that the visual system of lower primates is sufficiently similar to our own, electrophysiological techniques allow us to trace the production of neuroelectric currents in the visual nervous system, and thus to make conclusions offunction based on signal analysis. These techniques (pattern and luminance electroretinograms, and visual evoked potentials) are useful especially in delineating short-term effects (seconds). Since these signals are "large-scale" responses, their specificity can be set only by precisely delineating the stimuli used to evoke them, a variant of the GIGO (garbage in, garbage out) rule. The results, while obtainable in no other way, are therefore limited. Long-term effects (chronic alterations in visual function) can also be demonstrated with these techniques. This paper reviews both the techniques and the questions to which these techniques have been applied for laser exposure energies ranging from long-term low-level exposures to acute lesion-level exposures in the primate model.

The influence of polishing time on the roughness of ultrasmooth bowl-feed-polished surfaces is studied. A large improvement of the surface quality is obtained within the first 10 mm, but increasing the polishing time from 10 to 60 mm did not yield a significant difference. A Linnik interference miscroscope, adapted for phase-shifting interferometry, was used for roughness measurements. Preliminary measurements have been performed with a setup determining the scattered intensity within a small solid angle. This relatively simple setup, which is also suitable for uncoated glass surfaces, clearly showed the improvement of surface quality by bowl-feed polishing.

A two-component zoom system creates the necessary range of magnifications, fields of view, and focal lengths of any optical zoom system. Over the last few years the utilization of the zoom systems has significantly increased, but in developing these new optical designs, designers often unnecessarily complicate an existing solution rather than develop a new design form based on theory. The developing of opto-mechanical engineering demands the design of new types of modern zoom systems: systems with a long back focal length and telecentric chief rays in image space (e.g., Canon, Angenieux, Bosch). A grapho-analytical method for the first-order design of two-component zoom systems is developed. The canonic equation ofthe components' motion is presented. It is shown that law of motion is described by third-order hyperbolae of different types. The first-order correlations between system length, components' optical powers, and possible magnification range are given. The first-order data tables for the different two-component zoom systems are presented.

A single-source, single-detector architecture has been developed to implement a reconfigurable optical interconnection network for multimode optical fiber sensor arrays. The network was realized by integrating LiNbO₃ electro-optic (EO) gratings working at the Raman Nath regime and a massive fan-out waveguide hologram (WH) working at the Bragg regime onto a multimode glass waveguide. The glass waveguide utilized the whole substrate as a guiding medium. A 1-to-59 massive waveguide fan-out was demonstrated using a WH operating at 514 nm. Measured diffraction efficiency of 59% was experimentally confirmed. Reconfigurability of the interconnection was carried out by generating an EO grating through an externally applied electric field. Unlike conventional single-mode integrated optical devices, the guided mode demonstrated here has an azimuthal symmetry in mode profile which is the same as that of a fiber mode.

The subnanosecond operation of fast all-optical inverter gates has been investigated. Typical samples are 500- to 800-μm Cd_0.96Zn_0.04Te platelets without a Fabry-Pérot cavity thermalized around 80 K. Input and output beams operate at the same wavelength. The transmission of the sample is studied around the material band-gap energy (E_G = 1.613 eV, i.e., λ = 768 nm) versus the pump intensity. All-optical inversion is observed, based on a nonlinear absorption that appears below the band gap in the picosecond regime. The best switch energy is typically 3 to 5 pJ/μm² (i.e., 0.3 to 0.5 mJ/cm²) around the wavelength λ = 782 nm. From the analysis of the sample transmission under excitation, the possibility of stable operations with a good contrast of 4:1 between the high and the low logical states is shown. An optical amplifier has been combined with the inverter to get an output level as high as the input. The operation of the gate-amplifier stage that is cascadable with a contrast better than 2:1 is demonstrated.

An optical particle sizer utilizing an iterative procedure, proposed originally by Chahine for the inversion of scattering data, has been developed. The optical scheme is innovative and allows the measuring range to be selected without substitution of the Fourier transform lens. Numerical computer simulations and experimental results are presented to allow both the inversion procedure validity and the instrument performance to be evaluated.

This PDF file contains the editorial “Book Rvw: Optical Fiber Communications," by Gerd Keiser for OE Vol. 31 Issue 05

This PDF file contains the editorial “Book Rvw: Principles of Adaptive Optics," by Robert K. Tyson for OE Vol. 31 Issue 05