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The concept of fractional Fourier transform and its applications is discussed. The fractional Fourier transforms has several applications in the area, analog optical information processing, or Fourier optics. Fourier optical systems can be analyzed using geometrical optics, Fresnel integrals (spherical wave expansions), and plane wave expansions. The class of Fourier optical systems (or first order optical systems) consist of arbitrary thin filters lies in between arbitrary quadratic-phase systems. Quadratic graded-index media have a natural and direct relationship with the fractional Fourier transform. Light is simply fractional Fourier transformed as it propagates through quadratic graded-index media. Quadratic graded-index media realize fractional Fourier transforms in their purest and simplest form. The fractional Fourier transform can describe all systems composed of an arbitrary number of lenses separated by arbitrary distances, whereas imaging and Fourier transforming systems are only special cases.

Fractional Fourier Transform are introduced as sparsifying transforms.Linear Canonical Transforms are introduced as sparsifying transforms.Various approaches for compressing three-dimensional images are suggested. Display Omitted Sparse recovery aims to reconstruct signals that are sparse in a linear transform domain from a heavily underdetermined set of measurements. The success of sparse recovery relies critically on the knowledge of transform domains that give compressible representations of the signal of interest. Here we consider two- and three-dimensional images, and investigate various multi-dimensional transforms in terms of the compressibility of the resultant coefficients. Specifically, we compare the fractional Fourier (FRT) and linear canonical transforms (LCT), which are generalized versions of the Fourier transform (FT), as well as Hartley and simplified fractional Hartley transforms, which differ from corresponding Fourier transforms in that they produce real outputs for real inputs. We also examine a cascade approach to improve transform-domain sparsity, where the Haar wavelet transform is applied following an initial Hartley transform. To compare the various methods, images are recovered from a subset of coefficients in the respective transform domains. The number of coefficients that are retained in the subset are varied systematically to examine the level of signal sparsity in each transform domain. Recovery performance is assessed via the structural similarity index (SSIM) and mean squared error (MSE) in reference to original images. Our analyses show that FRT and LCT transform yield the most sparse representations among the tested transforms as dictated by the improved quality of the recovered images. Furthermore, the cascade approach improves transform-domain sparsity among techniques applied on small image patches.

We focus on the problem of representing a nonstationary finite-energy random field, with finitely many samples. We do not require the field to be of finite extent or to be bandlimited. We propose an optimizable procedure for obtaining a finite-sample representation of the given field. We estimate the reconstruction error of the procedure, showing that it is the sum of the truncation errors in the space and frequency domains. We also optimize the truncation parameters analytically and present the resultant Pareto-optimal tradeoff curves involving the error in reconstruction and the sample count, for several examples. These tradeoff curves can be used to determine the optimal sampling strategy in a practical situation based on the relative importance of error and sample count for that application.

We consider the problem of recovering a signal from partial and redundant information distributed over two fractional Fourier domains. This corresponds to recovering a wave field from two planes perpendicular to the direction of propagation in a quadratic-phase multilens system. The distribution of the known information over the two planes has a significant effect on our ability to accurately recover the field. We observe that distributing the known samples more equally between the two planes, or increasing the distance between the planes in free space, generally makes the recovery more difficult. Spreading the known information uniformly over the planes, or acquiring additional samples to compensate for the redundant information, helps to improve the accuracy of the recovery. These results shed light onto redundancy and information relations among the given data for a broad class of systems of practical interest, and provide a deeper insight into the underlying mathematical problem.

Cataloged from PDF version of article. We deal with the problem of efficient and accurate digital computation of the samples of the linear canonical transform (LCT) of a function, from the samples of the original function. Two approaches are presented and compared. The first is based on decomposition of the LCT into chirp multiplication, Fourier transformation, and scaling operations. The second is based on decomposition of the LCT into a fractional Fourier transform followed by scaling and chirp multiplication. Both algorithms take similar to N log N time, where N is the time-bandwidth product of the signals. The only essential deviation from exactness arises from the approximation of a continuous Fourier transform with the discrete Fourier transform. Thus, the algorithms compute LCTs with a performance similar to that of the fast Fourier transform algorithm in computing the Fourier transform, both in terms of speed and accuracy.

Optical fields propagating through quadratic-phase systems (QPSs) can be modeled as magnified fractional Fourier transforms (FRTs) of the input field, provided we observe them on suitably defined spherical reference surfaces. Non-redundant representation of the fields with the minimum number of samples becomes possible by appropriate choice of sample points on these surfaces. Longitudinally, these surfaces should not be spaced equally with the distance of propagation, but with respect to the FRT order. The non-uniform sampling grid that emerges mirrors the fundamental structure of propagation through QPSs. By providing a means to effectively handle the sampling of chirp functions, it allows for accurate and efficient computation of optical fields propagating in QPSs. © 2015 Elsevier B.V. All rights reserved.

The cause and amount of error arising from the use of the scalar approximation in monochromatic optical wave propagation are discussed using a signals and systems formulation. Based on Gauss’s Law, the longitudinal component of an electric field is computed from the transverse components by passing the latter through a two input single output linear shift-invariant system. The system is analytically characterized both in the space and frequency domains. For propagating waves, the large response for the frequencies near the limiting wave number indicates the small angle requirement for the validity of the scalar approximation. Also, a discrete simulator is developed to compute the longitudinal component from the transverse components for monochromatic propagating electric fields. The simulator output helps to evaluate the validity of the scalar approximation when the system output cannot be analytically calculated. © 2016 Informa UK Limited, trading as Taylor & Francis Group.

Cataloged from PDF version of article. Diffraction and holography are fertile areas for application of signal theory and processing. Recent work on 3DTV displays has posed particularly challenging signal processing problems. Various procedures to compute Rayleigh-Sommerfeld, Fresnel and Fraunhofer diffraction exist in the literature. Diffraction between parallel planes and tilted planes can be efficiently computed. Discretization and quantization of diffraction fields yield interesting theoretical and practical results, and allow efficient schemes compared to commonly used Nyquist sampling. The literature on computer-generated holography provides a good resource for holographic 3DTV related issues. Fast algorithms to compute Fourier, Walsh-Hadamard, fractional Fourier, linear canonical, Fresnel, and wavelet transforms, as well as optimization-based techniques such as best orthogonal basis, matching pursuit, basis pursuit etc., are especially relevant signal processing techniques for wave propagation, diffraction, holography, and related problems. Atomic decompositions, multiresolution techniques, Gabor functions, and Wigner distributions are among the signal processing techniques which have or may be applied to problems in optics. Research aimed at solving such problems at the intersection of wave optics and signal processing promises not only to facilitate the development of 3DTV systems, but also to contribute to fundamental advances in optics and signal processing theory. © 2007 IEEE.

Cataloged from PDF version of article. The problem of recovering a complex signal from the magnitudes of two of its fractional Fourier transforms is addressed. This corresponds to phase retrieval from the transverse intensity profiles of an optical field at two arbitrary locations along the optical axis. The convergence of the iterative algorithm, the effects of noise or measurement errors, and their dependence on the fractional transform order are investigated. It is observed that in general, better results are obtained when the fractional transform order is close to unity and poorer results are obtained when the order is close to zero. It follows that to the extent that conditions allow, the fractional order between the two measurement planes should be chosen as close to unity (or other odd integer) as possible for best results. (C) 2004 Elsevier B.V. All rights reserved.

Filtering in a single time domain or in a single frequency domain has recently been generalized to filtering in a single fractional Fourier domain. In this paper, we further generalize this to repeated filtering in consecutive fractinal Fourier domains. We then discuss the applications of the repeated filtering method to signal restoration through several examples. In all of the examples, we see that when our repeated filtering method is compared with single domain filtering methods, significant improvements in performance are obtained with only modest increases in processing time. We also compare our method with the optimum general linear estimation method and see that the use of our method may result in significant computational savings while still yielding acceptable performance.

Previously suggested systems for linear processing of temporal pulses are limited to time-invariant (convolution-type) operations. Although these are the most general operations possible with passive components, we show that by using nonlinear optical interactions, arbitrary linear operations can be performed. Such operations may be useful for performing time-variant analog signal processing, temporal matrix-vector multiplication, and time-slot interchange of pulses for digital communications systems.

Cataloged from PDF version of article. An algorithm for efficient and accurate computation of the fractional Fourier transform is given. For signals with time-bandwidth product N, the presented algorithm computes the fractional transform in O( N log N) time. A definition for the discrete fractional Fourier transform that emerges from our analysis is also discussed.

Our aim in this paper is to obtain the best synthesis of a desired mutual intensity distribution, by filtering in fractional Fourier domains. More specifically, we find the optimal fractional-domain filter that transforms a given (source) mutual intensity distribution into the desired one as closely as possible (in the minimum mean-square error sense). It is observed that, in some cases, closer approximations to the desired profile can be obtained by filtering in fractional Fourier domains, in comparison to filtering in the ordinary space or frequency domains.

In this article we consider the representation of a finite-energy non-stationary random field with a finite number of samples. We pose the problem as an optimal sampling problem where we seek the optimal sampling interval under the mean-square error criterion, for a given number of samples. We investigate the optimum sampling rates and the resulting trade-offs between the number of samples and the representation error. In our numerical experiments, we consider a parametric non-stationary field model, the Gaussian-Schell model, and present sampling schemes for varying noise levels and for sources with varying numbers of degrees of freedom. We discuss the dependence of the optimum sampling interval on the problem parameters. We also study the sensitivity of the error to the chosen sampling interval. (C) 2013 Elsevier Inc. All rights reserved.

We show how to explicitly determine the space-frequency window (phase-space window) for optical systems consisting of an arbitrary sequence of lenses and apertures separated by arbitrary lengths of free space. If the space-frequency support of a signal lies completely within this window, the signal passes without information loss. When it does not, the parts that lie within the window pass and the parts that lie outside of the window are blocked, a result that is valid to a good degree of approximation for many systems of practical interest. Also, the maximum number of degrees of freedom that can pass through the system is given by the area of its space-frequency window. These intuitive results provide insight and guidance into the behavior and design of systems involving multiple apertures and can help minimize information loss.

Cataloged from PDF version of article. It is customary to define a phase space such that position and momentum are mutually orthogonal coordinates. Associated with these coordinates, or domains, are the position and momentum operators. Representations of the state vector in these coordinates are related by the Fourier transformation. We consider a continuum of “fractional” domains making arbitrary angles with the position and momentum domains. Representations in these domains are related by the fractional Fourier transformation. We derive transformation, commutation, and uncertainty relations between coordinate multiplication, differentiation, translation, and phase shift operators making arbitrary angles with each other. These results have a simple geometric interpretation in phase space and applications in quantum optics.

Cataloged from PDF version of article. Previous optical implementations of the two-dimensional fractional Fourier transform have assumed identical transform orders in both dimensions. We let the orders in the two orthogonal dimensions to be different and present general design formulae for optically implementing such transforms. This design formulae allows us to specify the two orders and the input, output scale parameters simultaneously.

This work presents a linear algebraic theory of partial coherence for optical fields of continuous variables. This approach facilitates use of linear algebraic techniques and makes it possible to precisely define the concepts of incoherence and coherence in a mathematical way. We have proposed five scalar measures for the degree of partial coherence. These measures are zero for incoherent fields, unity for fully coherent fields, and between zero and one for partially coherent fields. � 2016 Optical Society of America.

Cataloged from PDF version of article. We present muchbriefer and more direct and transparent derivations of some sampling and series expansion relations for fractional Fourier and other transforms. In addition to the fractional Fourier transform, the method can also be applied to the Fresnel, Hartley, and scale transform and other relatives of the Fourier transform. (C) 2003 Published by Elsevier B.V

Cataloged from PDF version of article. We consider the problem of representation of a finite-energy optical field, with a finite number of bits. The optical field is represented with a finite number of uniformly spaced finite-accuracy samples (there is a finite number of amplitude levels that can be reliably distinguished for each sample). The total number of bits required to encode all samples constitutes the cost of the representation. We investigate the optimal number and spacing of these samples under a total cost budget. Our framework reveals the trade-off between the number, spacing, and accuracy of the samples. When we vary the cost budget, we obtain trade-off curves between the representation error and the cost budget. We also discuss the effect of degree of coherence of the field. © 2012 Optical Society of America

Cataloged from PDF version of article. Calculation of the scalar diffraction field over the entire space from a given field over a surface is an important problem in computer generated holography. A straightforward approach to compute the diffraction field from field samples given on a surface is to superpose the emanated fields from each such sample. In this approach, possible mutual interactions between the fields at these samples are omitted and the calculated field may be significantly in error. In the proposed diffraction calculation algorithm, mutual interactions are taken into consideration, and thus the exact diffraction field can be calculated. The algorithm is based on posing the problem as the inverse of a problem whose formulation is straightforward. The problem is then solved by a signal decomposition approach. The computational cost of the proposed method is high, but it yields the exact scalar diffraction field over the entire space from the data on a surface. © 2011 Elsevier B.V. All rights reserved.

We consider the transmission of a Gaussian vector source over a multi-dimensional Gaussian channel where a random or a fixed subset of the channel outputs are erased. Within the setup where the only encoding operation allowed is a linear unitary transformation on the source, we investigate the MMSE performance, both in average, and also in terms of guarantees that hold with high probability as a function of the system parameters. Under the performance criterion of average MMSE, necessary conditions that should be satisfied by the optimal unitary encoders are established and explicit solutions for a class of settings are presented. For random sampling of signals that have a low number of degrees of freedom, we present MMSE bounds that hold with high probability. Our results illustrate how the spread of the eigenvalue distribution and the unitary transformation contribute to these performance guarantees. The performance of the discrete Fourier transform (DFT) is also investigated. As a benchmark, we investigate the equidistant sampling of circularly wide-sense stationary (c.w.s.s.) signals, and present the explicit error expression that quantifies the effects of the sampling rate and the eigenvalue distribution of the covariance matrix of the signal. These findings may be useful in understanding the geometric dependence of signal uncertainty in a stochastic process. In particular, unlike information theoretic measures such as entropy, we highlight the basis dependence of uncertainty in a signal with another perspective. The unitary encoding space restriction exhibits the most and least favorable signal bases for estimation., Accepted for publication in IEEE Transactions on Information Theory

Computation of a binary spatial light modulator (SLM) pattern that generates a desired light field is a challenging quantization problem for which several algorithms have been proposed, mainly for far-field or Fourier plane reconstructions. We study this problem assuming that the desired light field is synthesized within a volumetric region in the non-far-field range after free space propagation from the SLM plane. We use Fresnel and Rayleigh-Sommerfeld scalar diffraction theories for propagation of light. We show that, when the desired field is confined to a sufficiently narrow region of space, the ideal gray-level complex-valued SLM pattern generating it becomes sufficiently low pass (oversampled) so it can be successfully halftoned into a binary SLM pattern by solving two decoupled real-valued constrained halftoning problems. Our simulation results indicate that, when the synthesis region is considered, the binary SLM is indistinguishable from a lower resolution full complex gray-level SLM. In our approach, free space propagation related computations are done only once at the beginning, and the rest of the computation time is spent on carrying out standard image halftoning. (C) 2011 Optical Society of America

Cataloged from PDF version of article. The course Science, Technology, and Society is taken by about 500 engineering students each year at Bilkent University, Ankara. Aiming to complement the highly technical engineering programs, it deals with the ethical, social, cultural, political, economic, legal, environment and sustainability, health and safety, reliability dimensions of science, technology, and engineering in a multidisciplinary fashion. The teaching philosophy and experiences of the instructor are reviewed. Community research projects have been an important feature of the course. Analysis of teaching style based on a multi-dimensional model is given. Results of outcome measurements performed for ABET assessment are provided. Challenges and solutions related to teaching a large class are discussed.

Imperfections and nonrobust behavior of practical multilevel spatial light modulators (SLMs) degrade the performance of many proposed full-complex amplitude modulation schemes. We consider the use of more robust binary SLMs for this purpose. We propose a generic method, by which, out of K binary (or 1 bit) SLMs of size M x N, we effectively create a new 2(K)-level (or K bit) SLM of size M x N. The method is a generalization of the well-known concepts of bit plane representation and decomposition for ordinary gray scale digital images and relies on forming a properly weighted superposition of binary SLMs. When K is sufficiently large, the effective SLM can be regarded as a full-complex one. Our method is as efficient as possible from an information theoretical perspective. A 4f system is discussed as a possible optical implementation. This 4f system also provides a means for eliminating the undesirable higher diffraction orders. The components of the 4f system can easily be customized for different production technologies. (C) 2011 Optical Society of America

Various methods of simulating diffusion phenomena with parallel hardware are discussed. In particular methods are compared requiring local and global communication among the processors in terms of total computation time. Systolic convolution on a locally connected array is seen to exhibit an asymptotic advantage over Fourier methods on a globally connected array. Whereas this may translate into a numerical advantage for extremely large numbers of ultrafast devices for two-dimensional systems, this is unlikely for three-dimensional systems. Thus global Fourier methods will be advantageous for three-dimensional systems for foreseeable device speeds and system sizes. The fact that optical interconnections are potentially advantageous for implementing the longer connections of such globally connected systems suggests that they can be beneficially employed in future nanoelectronic computers. Heat removal considerations play an important role in our conclusions.

Based on idealized interconnect scaling rules, we derive the optimal distribution of linewidths as a function of length for wire-limited layouts utilizing RC-limited interconnections. We show that the width of the wires should be chosen proportional to the cube root of their length for two-dimensional layouts and proportional to the fourth root of their length for full three-dimensional layouts so as to minimize average signal delay.

The analogy between optical one-to-one point transformations and optical one-to-one interconnections is discussed. Methods for performing both operations are reviewed and compared. The multifacet and multistage architectures have the flexibility to implement any arbitrary one-to-one transformation or interconnection pattern. The former would be preferred for low-cost and low-resolution applications, whereas the latter would be preferred for high-cost and high-performance applications.

A fast and accurate algorithm is developed for the numerical computation of the family of complex linear canonical transforms (CLCTs), which represent the input-output relationship of complex quadratic-phase systems. Allowing the linear canonical transform parameters to be complex numbers makes it possible to represent paraxial optical systems that involve complex parameters. These include lossy systems such as Gaussian apertures, Gaussian ducts, or complex graded-index media, as well as lossless thin lenses and sections of free space and any arbitrary combinations of them. Complex-ordered fractional Fourier transforms (CFRTs) are a special case of CLCTs, and therefore a fast and accurate algorithm to compute CFRTs is included as a special case of the presented algorithm. The algorithm is based on decomposition of an arbitrary CLCT matrix into real and complex chirp multiplications and Fourier transforms. The samples of the output are obtained from the samples of the input in approximately N log N time, where N is the number of input samples. A space-bandwidth product tracking formalism is developed to ensure that the number of samples is information-theoretically sufficient to reconstruct the continuous transform, but not unnecessarily redundant.

Linear canonical transforms (LCTs) form a three-parameter family of integral transforms with wide application in optics. We show that LCT domains correspond to scaled fractional Fourier domains and thus to scaled oblique axes in the space-frequency plane. This allows LCT domains to be labeled and ordered by the corresponding fractional order parameter and provides insight into the evolution of light through an optical system modeled by LCTs. If a set of signals is highly confined to finite intervals in two arbitrary LCT domains, the space-frequency (phase space) support is a parallelogram. The number of degrees of freedom of this set of signals is given by the area of this parallelogram, which is equal to the bicanonical width product but usually smaller than the conventional space-bandwidth product. The bicanonical width product, which is a generalization of the space-bandwidth product, can provide a tighter measure of the actual number of degrees of freedom, and allows us to represent and process signals with fewer samples.

We report a fast and accurate algorithm for numerical computation of two-dimensional non-separable linear canonical transforms (2D-NS-LCTs). Also known as quadratic-phase integrals, this class of integral transforms represents a broad class of optical systems including Fresnel propagation in free space, propagation in graded-index media, passage through thin lenses, and arbitrary concatenations of any number of these, including anamorphic/astigmatic/non-orthogonal cases. The general two-dimensional non-separable case poses several challenges which do not exist in the one-dimensional case and the separable two-dimensional case. The algorithm takes approximately N log N time, where N is the two-dimensional space-bandwidth product of the signal. Our method properly tracks and controls the space-bandwidth products in two dimensions, in order to achieve information theoretically sufficient, but not wastefully redundant, sampling required for the reconstruction of the underlying continuous functions at any stage of the algorithm. Additionally, we provide an alternative definition of general 2D-NS-LCTs that shows its kernel explicitly in terms of its ten parameters, and relate these parameters bidirectionally to conventional ABCD matrix parameters.

We are concerned with the problem of optimally measuring an accessible signal under a total cost constraint, in order to estimate a signal which is not directly accessible. An important aspect of our formulation is the inclusion of a measurement device model where each device has a cost depending on the number of amplitude levels that the device can reliably distinguish. We also assume that there is a cost budget so that it is not possible to make a high amplitude resolution measurement at every point. We investigate the optimal allocation of cost budget to the measurement devices so as to minimize estimation error. This problem differs from standard estimation problems in that we are allowed to design the number and noise levels of the measurement devices subject to the cost constraint. Our main results are presented in the form of tradeoff curves between the estimation error and the cost budget. Although our primary motivation and numerical examples come from wave propagation problems, our formulation is also valid for other measurement problems with similar budget limitations where the observed variables are related to the unknown variables through a linear relation. We discuss the effects of signal-to-noise ratio, distance of propagation, and the degree of coherence (correlation) of the waves on these tradeoffs and the optimum cost allocation. Our conclusions not only yield practical strategies for designing optimal measurement systems under cost constraints, but also provide insights into measurement aspects of certain inverse problems. Scientific and Technological Research Council of Turkey (TÜBİTAK)

Several approaches to three-dimensional integration of conventional electronic circuits have been pursued recently. To determine whether the advantages of optical interconnections are negated by these advances, we compare the limitations of fully three-dimensional systems interconnected with optical, normally conducting, repeatered normally conducting, and superconducting interconnections by showing how system-level parameters such as signal delay, bandwidth, and number of computing elements are related. In particular, we show that the duty ratio of pulses transmitted on terminated transmission lines is an important optimization parameter that can be used to trade off signal delay and bandwidth so as to optimize applicable measures of performance or cost, such as minimum message delay in parallel computation.

The problem of recovering signals from partial fractional Fourier transform information arises in wave propagation problems where the measured information is partial, spread over several observation planes, or not of sufficient spatial resolution or accuracy. This problem can be solved with the method of projections onto convex sets, with the convergence of the iterative algorithm being assured. Several prototypical application scenarios and simulation examples are presented.

Computation of the diffraction field from a given set of arbitrarily distributed data points in space is an important signal processing problem arising in digital holographic 3D displays. The field arising from such distributed data points has to be solved simultaneously by considering all mutual couplings to get correct results. In our approach, the discrete form of the plane wave decomposition is used to calculate the diffraction field. Two approaches, based on matrix inversion and on projections on to convex sets (POCS), are studied. Both approaches are able to obtain the desired field when the number of given data points is larger than the number of data points on a transverse cross-section of the space. The POCS-based algorithm outperforms the matrix-inversion-based algorithm when the number of known data points is large. © 2006 Elsevier B.V. All rights reserved.

The fractional Fourier transform is a signal processing tool which is strongly associated with optical data manipulation. It has fast computational algorithms and it suggests solutions to interesting signal processing tasks. In this paper we review its properties as well as present a new set of its applications for blind source separation of images and for RF photonics (a field in which photonic devices are used to process RF signals). © 2007 Pleiades Publishing, Ltd.

Date of Conference: 4-8 September 2005 Conference Name: 13th European Signal Processing Conference, EUSIPCO 2005 Image capture and image display will most likely be decoupled in future 3DTV systems. For this reason, as well as the need to convert abstract representations to display driver signals, and the need to explicitly consider diffraction and propagation effects, it is expected that signal processing issues will play a fundamental role in achieving 3DTV operation. Since diffraction between two parallel planes is equivalent to a 2D linear shift-invariant system, various signal processing techniques play an important role. Diffraction between tilted planes can also be modeled as a relatively simple system, leading to efficient discrete computations. Two fundamental problems are digital computation of the optical field due to a 3D object, and finding the driver signals for a given optical device so as to generate the desired optical field in space. The discretization of optical signals leads to several interesting issues; for example, it is possible to violate the Nyquist rate while sampling, but still maintain full reconstruction. The fractional Fourier transform is another signal processing tool which finds application in optical wave propagation.

Rent's rule and related concepts of connectivity such as dimensionality, line-length distributions, and separators are discussed. Generalizations for systems for which the Rent exponent is not constant throughout the interconnection hierarchy are provided. The origin of Rent's rule is stressed as resulting from the embedding of a high-dimensional information flow graph to two- or three-dimensional physical space. The applicability of these concepts to free-space optically interconnected systems is discussed. The role of Rent's rule in fundamental studies of different interconnection media, including superconductors and optics, is briefly reviewed. © 2004 Elsevier Inc. All rights reserved.

The problem of enhancing the resolution of wavefield or beam profile measurements obtained using low resolution sensors is addressed by solving the problem of interpolating signals from partial fractional Fourier transform information in several domains. The iterative interpolation algorithm employed is based on the method of projections onto convex sets (POCS).

Continuum extensions of common dual pairs of operators are presented and consolidated, based on the fractional Fourier transform. In particular, the fractional chirp multiplication, fractional chirp convolution, and fractional scaling operators are defined and expressed in terms of their common nonfractional special cases, revealing precisely how they are interpolations of their conventional counterparts. Optical realizations of these operators are possible with use of common physical components. These three operators can be interpreted as fractional lenses, fractional free space, and fractional imaging systems, respectively. Any optical system consisting of an arbitrary concatenation of sections of free space and thin lenses can be interpreted as a fractional imaging system with spherical reference surfaces. As a special case, a system departing from the classical single-lens imaging condition can be interpreted as a fractional imaging system. © 2003 Optical Society of America.

On approximating sums by maximums and vice versa We discuss the approximation max (x, y) ≈ x + y for x, y > 0, which is found to be useful in obtaining simple and transparent approximate solutions and interpretations for analytically complicated problems.

Self Fourier functions and fractional Fourier transforms are two concepts that have been discussed recently. Investigated is the combination of these two concepts: self fractional Fourier functions and the fractional Fourier transform of a self Fourier function.

Owing to the nonlinear nature of the problem, the transform orders in fractional Fourier-domain filtering configurations have usually not been optimized but chosen uniformly. We discuss the optimization of these orders for multi-channel-filtering configurations by first finding the optimal filter coefficients for a larger number of uniformly chosen orders, and then maintaining the most important ones. The method is illustrated with the problem of synthesizing desired mutual-intensity distributions. The method we propose allows those fractional Fourier domains, which add little benefit to the filtering process but increase the overall cost, to be pruned, so that comparable performance can be attained with less cost, or higher performance can be obtained with the same cost. The method we propose is more likely to be useful when confronted with low-cost rather than high-performance applications, because larger improvements are obtained when the use of a smaller number of filters is desired. (C) 2002 Optical Society of America.

We present a linear algebraic theory of partial coherence which allows precise mathematical definitions of concepts such as coherence and incoherence. This not only provides new perspectives and insights, but also allows us to employ the tools of linear algebra in applications. We define a scalar measure of the degree of partial coherence of an optical field which is zero for complete incoherence and unity for full coherence. 1. INTRODUCTION The theory of partial coherence is a well established area of optics."2 In this work, we formulate the theory interms of the standard concepts of linear algebra, leading to a number of new perspectives. While not containing any new physics, this approach offers new insights, understanding, and operationality and has the potentialto facilitate applications, especially in optical information processing. In this paper we consider the case of discrete light fields, which lead to a particularly simple matrix-algebraic formulation. Once the framework isestablished, it is not difficult to translate the matrix formalism for discrete fields to a continuous formalism. Werestrict our attention to quasi-monochromatic conditions. One-dimensional notation is employed for simplicity.

The ath-order fractional Fourier transform is a generalization of the ordinary Fourier transform such that the zeroth-order fractional Fourier transform operation is equal to the identity operation and the first-order fractional Fourier transform is equal to the ordinary Fourier transform. This paper discusses the relationship of the fractional Fourier transform to harmonic oscillation; both correspond to rotation in phase space. Various important properties of the transform are discussed along with examples of common transforms. Some of the applications of the transform are briefly reviewed.

It is shown that the space-bandwidth product of conventional “2 f ” Fourier transforming configurations can be increased without bound by increasing the diameter D and focal length f of the lens simultaneously to D∝f 3 4 . This results in space-bandwidth product growth ∝f 1 2 and accompanying system linear extent growth ∝f 3 4 . These are derived by considering the validity of the Fresnel approximation, the thin lens approximation, and the effects of aberrations.

In this communication we propose performing two-dimensional correlation operation between phase-space representations based on the fractional Fourier transform, instead of correlating the signals themselves. A numerical examples clearly indicates superior discrimination performance. (C) 2001 Published by Elsevier Science B.V.

Perspective projections in the space-frequency plane are analyzed, and it is shown that under certain conditions they can he approximately modeled in terms of the fractional Fourier transform, The region of validity of the approximation is examined. Numerical examples are presented. (C) 2000 Optical Society of America

We discuss the application of fractional Fourier transform-based filtering configurations to image representation and compression. An image can be approximately represented (and stored or transmitted) as the coefficients of the minimum mean square filtering configuration approximating the image matrix. An order of magnitude compression is possible with moderate errors with the raw method. While inferior to commonly available compression algorithms, the results presented correspond to the basic method without any refinement or combination with other techniques, suggesting that the approach may hold promise for future development. Regardless of its practical usefulness, the fact that the information inherent in an image can be decomposed or factored into fractional Fourier domains is of considerable conceptual significance. The information contained in the image is distributed to the different domains in an unequal way, making some domains more dispensible than others in representing the image. (C) 2001 Published by Elsevier Science B.V.