We survey recently invented methods of optical tomographic imaging through scattering medium. The three-dimensional structure of an object hidden between two biological tissues is recovered from many noisy speckle pictures obtained on the output of a multi-channeled optical imaging system.

Observing at a microscope object having a three-dimensional (3D) complex shape only a portion of it appears in focus since essentially a single image plane is imaged. Up to now only two approaches have been developed to obtain an extended focused image (EFI). An EFI shows all details of the object in focus. Both methods having severe limitations since one requires mechanical scanning while the other needs specially designed optics. We demonstrate that an EFI image of an object can be obtained by means of digital holography (DH) in a microscope configuration overcoming the mentioned limitations. The novelty of the proposed approach lies in the fact that it is possible to build an EFI by exploiting the unique feature of DH in extracting all the information content stored in hologram (phase and amplitude).

Wavelets are used extensively in image processing due to the localized frequency information that can be conveyed by the wavelet transform. This and other characteristics of wavelet transforms can be exploited very effectively for the compression of images. We apply the wavelet transform to digital holograms of three-dimensional objects. Our digital holograms are complex-valued signals captured using phase-shift interferometry. Speckle gives them a white noise-like appearance with little correlation between neighboring pixels. In our analyses we concentrate on the discrete wavelet transform and Haar dyadic bases. We achieve compression through quantization of the wavelet transform coefficients. We quantize the discrete wavelet coefficients in each of the subbands depending on the dynamic range of the coefficients in that subband. Finally, we losslessly encode these subbands to quantify the high compression ratios achieved. We outline the three issues that need to be dealt with in order to improve the compression ratio of wavelet based techniques for particular applications as (i) determining a good criterion for ascertaining the coefficients that have to be retained, (ii) determining a quantization strategy and quantization error appropriate to one's particular application, and (iii) compression of the bookkeeping data.

We present a technique to convert a digital hologram of a three-dimensional (3D) object into a cloud of surface points in 3D space. Two depth-from-defocus techniques are used to generate a depth map for a particular reconstructed perspective of the object encoded in the digital hologram. The Fresnel transform is used to effect defocus, and a histogram-based approach is used to determine the degree of defocus for each neighborhood of pixels. Our experiments involve simulated and real-world objects (captured using phase-shift digital interferometry). The technique could be used in registration and 3D object recognition applications.

We have successfully applied Independent Component Analysis to the removal of background speckle noise from digital holograms. Additive noise removal techniques do not perform well on speckle, which is better characterized as multiplicative noise. In addition, speckle contains 3D information and so cannot be removed completely. We use a blind source separation approach to the reduction of speckle noise in digital holograms. Independent Component Analysis computes a linear transformation of a multi-dimensional distribution that minimizes the statistical dependence between the components. It can be seen as an extension of principal component analysis where the transformed bases do not need to be orthonormal. Although a linear technique, we show how Independent Component Analysis can be applied to the reduction of background speckle in digital holograms. We have captured our digital holograms of three-dimensional objects using phase-shift digital interferometry. In addition, the technique can be extended and applied to segmentation and pattern recognition problems on digital holograms of three-dimensional objects. Results are provided using simulated and optical data.

In autostereoscopic display systems which are based on lenticular, barrier, and lens array plates, the quality of perceived images is different in different regions of the viewing zone. In these systems, a visual image is a composition of several view images which depends on the current observer position. A quantification of the visual quality is suggested basing on the inverse number of different view images involved in a composed visual image. This definition of the quality can only be applied directly to the monoscopic seeing. A new method to estimate the quality value for binocular seeing is therefore devised. It is based on the mapping of different regions of the viewing zone onto a uniform map. The map is scanned by virtual probes "equipped" with single/dual sensors expressing observer's eyes for mono/stereo seeing. The virtual readings of both type probes can be represented in a matrix form giving very similar values for both cases. We found a generalized analytical solution which estimates the image quality as a coordinate-dependent function for both, monoscopic and stereoscopic cases. The generalized solution does not depend on the individual interocular distance.

Recently, a two-dimension/three-dimension (2D/3D) convertible display system based on the integral imaging technique was proposed. The 2D/3D convertible system shares similar characteristics with integral imaging, but the analysis on the integral imaging cannot be directly applied to the 2D/3D convertible system. In this paper, the 2D/3D convertible display system is analyzed using wave optics to consider the effect of diffraction which plays an important role since the dimension of the 2D/3D convertible system is fairly small. First, the equation that governs the diffraction effect in the three-dimensional image display mode of the 2D/3D convertible system is derived assuming monochromatic and coherent point light source. Based on the equation, simulations and analyses of the 2D/3D convertible system are given.

Enhanced integral imaging system based on the image floating method is proposed. The integral imaging is one of the most promising methods among the autostereoscopic displays and the integrated image has the volumetric characteristics unlike the other stereoscopic images. The image floating is a common 3D display technique, which uses a big convex lens or a concave mirror to exhibit the image of a real object to the observer. The image floating method can be used to emphasize the viewing characteristics of the volumetric image and the noise image which is located on the fixed plane can be eliminated by the floating lens through the control of the focal length. In this paper, the solution of the seam noise and the image flipping of the integral imaging system is proposed using the image floating method. Moreover, the advanced techniques of the integral imaging system can be directly applied to the proposed system. The proposed system can be successfully applied to many 3D applications such as 3D television.

We propose robust three-dimensional (3D) object recognition method using a complex amplitude based on the Fourier transform profilometry (FTP) and the numerical holographic multiplexing. In the proposed method, a reference data for correlation operation is produced by multiplexing of the complex amplitude derived from several rotated objects, taking into account that the complex amplitude derived from rotated objects is mutually uncorrelated with respect to the rotation angle. Due to the use of the multiplex reference data, the correlation between each reference data to be multiplexed and a target object is performed with single operation. Therefore, the proposed method has tolerance to rotation in addition to translation due to the shift-invariant property of the FTP-based correlator. The spatial position and the orientation of the 3D object can be also evaluated by the proposed method. Experimental results show that the proposed method successfully recognizes the rotated 3D object.

To improve the image quality of the decrypted image through the double-random phase-encoding optical encryption, the design method of the input phase mask is proposed. The input phase mask is iteratively designed so that the extent of the Fourier spectrum of the product of an input image and the input phase mask matches to the space bandwidth of the optical system. By using the designed input phase mask, we show that the bit-error rate is improved. We also discuss the number of the phase levels of the designed input phase mask.

In this paper we present the first steps to an algorithm for effective compression of digital holograms. This algorithm is based on the properties of the electromagnetic field that generates the holograms. The investigation of the underlying physical behavior allows us a better reduction of the number of bits needed to compress the data. We show that the quantization in the frequency domain as contained in the extended JPEG compression is suitable for high quality compression of holograms. We present the application of this approach to holograms with low space-bandwidth products and perform a generalization to typical holograms with high space-bandwidth products. Our tests using simulated and real world holograms from different origins show approximately the same performance on the same levels of compression. This performance is better concerning the quality of the data compared to the one of the standard JPEG implementation and can be improved concerning the file size. While the visual impression of the intensity reconstruction is good even for 2bit compression, the reconstruction of the phase for higher compression ratios shows remarkable errors. In the future we want to better adopt our approach to the extended JPEG standard based in the way that we use 8x8 clusters instead of the whole image for quantization. This gives hope to further increase the reconstruction quality and the compression ratio in the future.

Phase retrieval is the recovery of missing phase information in an optical field using measurable quantities. Usually the directly measurable quantity in an optical system is the intensity of the image and a diffraction pattern. The Gerchberg-Saxton (GS) algorithm utilizes the spatial and the spatial frequency intensities and the Fourier Transform (FT) is used to numerically transform between the two. Recently the fractional Fourier transform (FRT) has been proposed in the same context. Studies have shown that the efficiency of this FRT based Gerchberg-Saxton algorithm is dependent upon the discrete FRT used in the procedure. If this discrete FRT is unitary optimum results are obtained. In this paper we investigate the use of a recently proposed set of theoretically unitary discrete FRT algorithms. These algorithms are based on tracking the shape of the signal's Wigner Distribution Function (WDF) and the relationship between this shape and the Space-Bandwidth Product (SBP). We provide numerical simulations and compare these with those obtained using the traditional FT-GS algorithm.

A simple method to obtain spatial multiplexing imaging is by using an array of imaging elements such as a lenslet or pinhole array. Using a lenslet array instead of a common imaging lens permits a more flexible design of the optical system and enables the control and enhancement of the imaging performance parameters. By proper design and appropriate optical data processing, multiple perspectives of a three dimensional object can be captured, the visual imaging range can be enlarged, the imaging resolution improved and depth of field extended. Lenslet arrays are the core of integral imaging systems which is a promising three dimensional imaging and visualization technique. In the context of three dimensional imaging, lenslet arrays serve as dense multiview imaging sensors. In this work we explore the potential advantages of imaging with a lenslet array. We discuss the inherent limitations and describe techniques to overcome those limitations. Here we focus our discussion on integral imaging systems and present an overview of techniques and approaches used to control and improve the performance of basic integral imaging systems.

The numerical calculation of the Fresnel Transform (FST) presents significant challenges due to the high sampling rate associated with the chirp function in the kernel. The development of a general algorithm is further complicated due the fact that the output extent of the FST is dependant on the propagation distance. In this paper we implement a novel technique for calculating the FST in which we use the Wigner Distribution Function (WDF) to choose an optimal sampling rate. This method is suitable for all propagation distances. Our method can also be used to describe the effect of a lens in an optical system. A lens in an optical system is modeled as a Chirp Modulation Transform (CMT), which acts on the spatial frequency distribution of a signal in a manner that is analogous to the effect an FST has on the spatial distribution of a signal. Combining our results for the FST and the CMT we numerically calculate the light distribution at the output of both a Cai-Wang and a Lohmann Type-I Optical Fractional Fourier Transform (OFRT) system. Analytic solutions for the OFRT of a square (1-D) and circular (1-D) aperture are presented. The numerical results are compared to the analytically derived solution.

Computers perform poorly in comparison with the human brain for everyday tasks because they evolved from a 1940's number crunching architecture. New architectures are needed, more appropriate for current everyday tasks: web database search, network communication and recognition. For a new computer architecture, we consider the Wilson Cowan biological neural network (BNN) model of the brain which couples excitatory and inhibitory neurons in an additive neural model with sigmoid nonlinearity. We analyze the Wilson Cowan equations to demonstrate supercritical Hopf bifurcation that switches the neural oscillator between off and a stable oscillation---a basic operation in the brain. To mimic the Wilson Cowan neuron, we propose a novel all-optical artificial neural network (ANN) architecture in which semiconductor optical amplifiers (SOAs) perform addition and provide optical injection to a laser diode. We analyze the proposed all-optical system to show that it also performs supercritical Hopf bifurcation, although in this case with 3-D time trajectories rather than 2-D ones. We conclude that the all-optical system has as much dynamic capability as the mathematical brain model. This research aims to stimulate the development of physical analogs to the brain for future computing and better understanding of the brain.

In order to realize the flexibility optical trapping offers as a nanoassembly tool, we need to develop natural and intuitive interfaces to assemble large quantities of nanocomponents quickly and cheaply. We propose a system to create such an interface that is scalable, inter-changeable and modular. Several prototypes are described, starting with simple interfaces that control a single trap in the optical tweezers instrument using a 3-dimensional Phantom haptic device. A networkbased approach is adopted early on, and a modular prototype is then described in detail. In such a design, individual modules developed on different platforms work independently and communicate with each other through a common language interface using the Neutral Messaging Language (NML) communication protocol. A natural user interface is implemented that can be used to create and manipulate traps interactively like in a CAD program. Modules such as image processing and automatic assembly are also added to help simplify routine assembly tasks. Drawing on lessons learned from the prototypes, a new system specification is formulated to better integrate the modules. Finally, conclusions are drawn on the overall viability and future of network-based systems for nanoassembly using optical tweezers.

In a previously reported holographic code for the synthesis of arbitrary complex fields with phase-only modulators, the amplitude is encoded by scaling the phase modulation. For the appropriate performance of this code, it is necessary to employ an ideal phase modulator, which can not be easily obtained with a standard liquid-crystal device. We generalize and improve the above holographic code in such a way that the desired complex function can be obtained by using the restricted phase-mostly modulation provided by a twisted-nematic liquid-crystal display, in a simple setup employing two polarizers and a He-Ne laser. A commercial liquid-crystal device employed in this setup only provides a phase modulation in a range smaller than 1.5π radians, coupled with an amplitude modulation with a significant variance. In spite of these restrictions, the quality of complex signals encoded with the modified holographic code is only affected by a marginal efficiency reduction. We present numerical simulations and experimental results regarding our proposal.

Three portable prototype devices for cardiovascular biosensing based on reflection-type photoplethysmography (PPG) principle have been designed and clinically tested. The single-channel PPG finger sensor provides real-time measurements with fast calculation of the mean single-period PPG signal shape ("cardiovascular fingerprint", potentially useful for recognition). The dual-channel PPG system gives additional possibility to monitor on-line the arterial pulse wave transit time and its responses to physical exercises. The four-channel PPG system proved to be applicable for fast detection of cardiovascular pathologies, e.g. arterial occlusions in extremities. Design principles and software algorithms of the regarded devices will be discussed, as well as the results of recent clinical tests.

Automatic recognition of objects independent of size, orientation, position in the field of view, and color is a difficult and important problem in computer vision, image analysis, and automatic target recognition fields. In this paper we explore the theory of invariant algebra to develop solutions for this problem. Algebraic invariants of binary and ternary quantics are used to obtain features that remain unchanged when the object undergoes linear geometrical and spectral transformations. Empirical examples of the use of this approach on real and synthetic data are provided.

The concept of Integrated Sensing and Processing (ISP) suggests that a sensor should collect data in a manner that is consistent with the end objective. Thus ISP seeks to minimize the collection of redundant data, reduce processing time and improve overall performance. We present a case study of ISP using a multi-spectral camera which allows the spatial resolution of the data to be varied in addition to selecting spectral bands that enable the detection of targets in background clutter. This paper is a preliminary description of work in progress, and illustrates the basic concepts by means of several examples.

A number of applications in security or inventory control may benefit from an authentication system able to identify a remote object viewed from different perspectives or distances. Object identification can be accomplished by using optical ID tags, which include relevant information of the target and are located on a visible part of the object under surveillance. Encryption of the information codified in the ID tag allows increasing security and deters from unauthorized usage of optical tags. The identification process encompasses several steps such as detection, information decoding and verification which are all detailed in this work. Design of distortion-invariant ID tags has to be taken into account to achieve a correct object authentication even if the ID tag is detected and captured at different distances (i.e. different scales) or from different views (i.e. rotated versions of the original ID tag). Description of diverse distortion-invariant ID tags and authentication results using the proposed ID tags are provided. We show that distortion-tolerance is achieved by the described identification system. Information encrypted on the tested ID tags is correctly decoded and verified even if variations in scale and rotations are considered. The effects of environmental degradation are taken into account in the recognition process.

The availability of high quality Spatial Light Modulators (SLMs) and high-resolution cameras have made it technologically feasible to perform many optical signal-processing functions in a relatively inexpensive manner. Furthermore, recent fast algorithms have been proposed to compute Linear Canonical Transforms (LCTs), which may be used to simulate paraxial optical systems. Optical Encryption offers the possibility of high-speed parallel encryption of image data. Such encryption/decryption may involve the capture of full field information, i.e. phase and intensity. Applications of Digital Holography go beyond applications to optical encryption. They include Holographic Interferometry (metrology) and Holographic displays. In this paper we discuss the design and analysis of systems used in the capture, encryption/decryption and display of 2-D (image) data and present our recent experimental and theoretical results.

Electrowetting is electrostatic manipulation of liquids. It can be used to displace and deform volumes of polar liquids. A very promising application area is optics. The surface of a volume of liquid can be used as a tunable lens and displacement of the liquid can change the refraction, diffraction or transmission of light when passing through the liquid. In this paper we describe a selection of various tunable optical components that make use of electrowetting, ranging from refractive and diffractive lenses to diaphragms and displays.

"Optofluidics" is the marriage of optics, optoelectronics and nanophotonics with fluidics. Such integration represents a new approach for dynamic manipulation of optical properties at length scales both greater than and smaller than the wavelength of light with applications ranging from reconfigurable photonic circuits to fluidically adaptable optics to high sensitivity bio-detection currently under development. The capabilities in terms of fluidic control, mixing, miniaturization and optical property tuning afforded by micro-, nano- and electro-fluidics combined with soft lithography based fabrication provides an ideal platform upon which to build such devices. In this paper we provide a general overview of some of the important issues related to the fabrication, integration and operation of optofluidic devices and present three comprehensive application examples: nanofluidically tunable photonic crystals, optofluidic microscopy and DFB dye lasers.

At the receiver of an ultrashort-pulse optical code-division multiple-access (OCDMA) system, a nonlinear thresholder is needed to discriminate between the correctly decoded short pulse and the interference that appears to be a pseudorandom signal. It has been demonstrated that the self phase modulation (SPM) effect can be used to realize this nonlinear thresholder. The performance of a system that exploits this phenomenon is analyzed in this paper. If the spreading code is random, the electrical field of the interfering signal from the multiple users can be shown to be a complex Gaussian random process. The broadened power spectral density (PSD) function caused by the SPM effect can be calculated. When "1" is transmitted, the correctly decoded signal from the desired user, which is a deterministic waveform, is added to the Gaussian random process. Beating between the two signals causes random fluctuations in the power. Since the strength of the SPM effect is proportional to the variation rate of power, the broadened signal spectrum will appear random. The Monte Carlo method is used to obtain the properties of the decision statistic. Finally, the bit-error rate (BER) is calculated, and the simulation results are presented. The result reveals that the performance of the SPM-based nonlinear receiver can outperform the ideal linear receiver in some circumstances.

The wavelength-hopping/time-spreading scheme for optical code-division multiple-access (OCDMA), also known as the 2-D scheme, has been studied by many researchers for more than a decade. In all of previous analyses, the light sources were modeled as perfectly incoherent, which requires infinite bandwidth, and chip-synchrony was assumed for mathematical simplicity. Therefore, it is important to study how the system actually performs with true asynchrony and practical light sources. The amplified spontaneous emission (ASE) source is a desirable source for the incoherent OCDMA system because of its broad bandwidth, large power, and low cost. In this paper, each chip generated by the transmitter is a rectangular ASE pulse with a Gaussian-distributed electrical field. The coherence time is much smaller than the chip duration, but non-zero. Because of this partial coherence of the light source, beat noise will occur when multiple pulses are combined. In addition, interfering pulses may only partially overlap with the pulses from the desired user due to the asynchrony, which introduces more randomness into the decision statistic. Both factors are taken into account when the distribution of the decision statistic is derived mathematically. Simulations of the bit-error rate (BER) are performed, and the results show that the coherence time may be the major limiting factor on the system performance. For example, when the coherence time is only 1/100 of the chip duration, the BER is 1-4 orders of magnitude worse than that of the ideal case.

We show improvement in the signal-to-noise ratio of speckle correlation fringe patterns by providing a conjugate phase to the scattered object beam. This conjugate phase negates the speckle phase and will leave the speckle intensity as the only statistically varying quantity. Since one of the random variables is reduced the signal-to-noise ratio improves. The variation of intensity in the fringe profile is reduced after the adaptive phase correction. This improvement is vividly seen after a simple morphological filtering. The experiment is performed using a twisted nematic liquid crystal display SLM in transmission.

When document images are obtained from digital cameras, many imaging problems have to be solved for better extraction of characters from the images. Variation of illumination intensity sensitively affects to color values. A simple colored document image could be converted to a monochrome image by a traditional method and then a binarization algorithm is used. But this method is not stably working to the variation of illumination because sensitivity of colors to variation of illumination. For narrowly distributed colors, the conversion is not working well. Secondly, in case that the number of colors is more than two, it is not easy to figure out which color is for character and which others are for background. This paper discusses about an extraction method from a colored document image using a color process algorithm based on characteristics of color features. Variation of intensities and color distribution are used to classify character areas and background areas. A document image is segmented into several color groups and similar color groups are merged. In final step, only two colored groups are left for the character and background. The extracted character areas from the document images are entered into optical character recognition system. This method solves a color problem, which comes from traditional scanner based OCR systems. This paper also describes the OCR system for character conversion of a colored document image. Our method is working for the colored document images of cellular phones and digital cameras in real world.

The binary joint transform correlator (BJTC) can provide sub-pixel correlation location accuracy for a pair of almost identical inputs, as is the case when computing the registration offset between two overlapping images from the same sensor. Applications include noise cancellation, motion compensation, super-resolution processing, and image splicing. We experimentally demonstrated sub-pixel registration and image co-addition. Our results show a resolution improves by a factor of almost two compared to normal integration. This paper details early results in an ongoing project.

In real-world pattern recognition applications, multiple correlation filters can be synthesized to recognize broad variation of object classes, viewing angles, scale changes, and background clutters. Composite filters are used to reduce the number of filters needed for a particular target recognition task. Conventionally, the correlation peak is thresholded to determine if a target is present. Due to the complexity of the objects and the unpredictability of the environment, false positive or false negative identification often occur. In this paper we present the use of a radial basis function neural network (RBFNN) as a post-processor to assist the optical correlator to identify the objects and to reject false alarms. Image plane features near the correlation peaks are extracted and fed to the neural network for analysis. The approach is capable of handling large number of object variations and filter sets. Preliminary experimental results are presented and the performance is analyzed.

We present a new technique for adaptive band selection from hyperspectral image cubes for detecting small targets using an anomaly detector. The proposed technique ensures the selection of lowest number of spectral bands using Mahalanobis distance, maximum affordable extra noise variance, and Constant False Alarm Rate (CFAR) anomaly detector threshold. Since the target is small, band selection based only on Mahalanobis distance is not adequate and the bands which can withstand extra noise should be chosen. In addition, thresholding must be considered to avoid misclassification of target. The proposed technique yields comparatively low false alarm rate even with a few bands. For real time applications, acousto-optic tunable filter based spectral imagers may be used for acquiring hyperspectral images and for selecting the bands.

In this paper, we propose a new optical implementation for reference-phase-encoded joint transform correlation technique for efficient multiple target detection. The proposed method employs phase encoding for the reference image and nonlinear Fourier plane apodization for optimizing the detection performance. The reference phase-encoded joint transform Correlator (JTC) overcomes false target detection by eliminating the false correlation peaks while alleviating the effects of noise and other artifacts in just one-step thus ensuring higher processing speed. This technique yields only one peak per target instead of a pair of peaks produced by alternate JTCs. An all-optical implementation for the reference phase-encoded JTC technique is proposed and experimental results are presented.

Face recognition is used in a wide range of security systems, such as monitoring credit card use, searching for individuals with street cameras via Internet and maintaining immigration control. There are still many technical subjects under study. For instance, the number of images that can be stored is limited under the current system, and the rate of recognition must be improved to account for photo shots taken at different angles under various conditions. We implemented a fully automatic Fast Face Recognition Optical Correlator (FARCO) system by using a 1000 frame/s optical parallel correlator designed and assembled by us. Operational speed for the 1: N (i.e. matching a pair of images among N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 seconds, including the pre/post processing. From trial 1: N identification experiments using FARCO, we acquired low error rates of 2.6% False Reject Rate and 1.3% False Accept Rate. By making the most of the high-speed data-processing capability of this system, much more robustness can be achieved for various recognition conditions when large-category data are registered for a single person. We propose a face recognition algorithm for the FARCO while employing a temporal image sequence of moving images. Applying this algorithm to a natural posture, a two times higher recognition rate scored compared with our conventional system. The system has high potential for future use in a variety of purposes such as search for criminal suspects by use of street and airport video cameras, registration of babies at hospitals or handling of an immeasurable number of images in a database.

The theoretical and the experimental researches of spectra of absent-minded radiation in medium containing viruses of the influenza, the hepatitis C and smallpox of the rabbit were carried out. The noises arising at a stage of generation of radiation in biological structure of a virus have been investigated. It has been shown, that the intensity of the parasitic luminescence is the least if solvent is alcohol and the greatest if solvent is water.

We demonstrated our newly designed architecture of optical self-organizing network which enables concurrent peer-to-peer communications of more than two pairs in our previous model. We have realized this architecture by expanding the previous two dimensional lattice connection into three dimensional lattice connection. Two main features achieved by our present work are as follows. First, we have designed the tubular shaped architecture of equivalent peer-to-peer type network which enables two pairs to perform transmission from any open ports located at each end of the tubular connected nodes. Secondly, we have considered to layer the tubular shaped network structure described above in order to increase the limit of pairs by which concurrent communications are possible. In numerical simulation, we have confirmed the efficiency of our above mentioned two architectures of networks. The merit of these two networks is that they can be composed by our previously reported three-port node we have simply realized in optoelectronic hardware or by just adding the fourth port to it. As a consequence, we have proved that our present scheme of simple architectures of optical self-organizing network has potential utility value in actual use for peer-to-peer optical communications.

The eigen-image correlation recognition method proposed for optical image recognition is utilized in this paper for optical iris recognition. The best basis selection of this method is modified by introducing new criterion for evaluating wavelet packet bases. Using the cascade algorithm, the 2-D approximations of wavelet packet basis functions are computed. And the direct transforms of these wavelet packet bases make the larger scale of basis selection possible. From the wavelet packet basis set of 25 mothers, multi-mother multi-vanishing moment joint best bases are chosen for iris recognition. Their eigen-images are generated for optical experiments. Based on these best bases, an optical wavelet packet gray scale filter is designed and fabricated to improve the optical recognition. In a volume holographic correlation system, optical experiment results show this filter is efficient to achieve higher identification rate.

In this paper, new configuration of inner optic module of LCD projectors for polarized stereoscopic projection with no light loss in the process of polarization is proposed. In the proposed system, two polarizing filters or waveplates, which have been employed in the conventional LCD polarized stereoscopic projection systems and consequently caused an additional light loss and image distortion, are excluded by modifying the inner optic module of LCD projectors and some steps of image processing, so that maximum light efficiency in the polarization process can be obtained from the proposed method.

In this paper, a novel method to generate computer-generated holograms(CGH) of a real three-dimensional(3D) object using stereoscopic video images is proposed. Stereoscopic video images of a real 3D object are captured with a 3D camera system and disparity maps between the left and right image pairs are estimated on the frame basis. Then, depth data for each pixel of the object can be extracted from these estimated disparity maps. Using these depth data and original color images, hologram patterns of a real object can be computationally generated. In the experiment with a 3D adaptor(3D58 LenSys, Wasol) system, stereoscopic images of a real 3D object of 'cup' are captured and its depth data are extracted from them. Then, CGH patterns are generated with these depth-annotated images of the 'cup' and experimentally displayed via a holographic display system.

Scatterometry is an optical measurement technology based on the analysis of light scattered, or diffracted, from a periodic array of features. It is not an optical imaging technique, but rather a model-based metrology that determines measurement results by comparing measured light scatter against a model of theoretical scatter 'signatures'. Conventional algorithms take the average of the difference between the experimental and modeled signatures across the full detection range, and calculate a fitting quality score parameter for the fit, eg. as a RMSE (Root Mean Square Error), MSE (Mean Square Error) or SD (Square Distance). This study reports a novel method for efficiently and accurately determining grating profiles using characteristic signature matching in a discrepancy-enhanced library generation process. Using light scattering theory, such as rigorous coupled wave theory, a series of scattering signatures vs. scattering angles or wavelengths are generated based on the designed grating parameters, eg. CD (Critical Dimension), thickness and Line:Space ratio. This method selects characteristic portions of the signatures wherever their measurement sensitivity exceeds the preset criteria and reforms a characteristic signature library for quick and accurate matching. This method does not need to modify existing measurement hardware or the grating target. It saves a great percentage of storage memory in the computer system, and also increases the measurement sensitivity.

Current optical overlay measurement tools utilize visible light and operate with optical resolution of approximately 0.5-1.0 μm. Such tools cannot resolve the targets based on the design rule features. Hence, reliable theoretical model-based measurements and enhanced algorithms are required to address this problem. The test targets, with features similar to those specified by the design rule, were fabricated by a high precision E-beam writer. An optical bright field overlay metrology tool was applied to acquire the optical images of the test targets. The best focus position of test target is selected using an auto focus algorithm. The focus offset is specified relative to the best focus position and the optical image data is measured with a full field-of-view CCD array. The through focus image data are analyzed to obtain the relationship between the intensity profile and the structural parameters of the test targets. These structural parameters are also verified with the CD-SEM. This work experimentally analyzes the through-focus behavior of the test targets. These targets are based on grating patterns, and while they provide more information than traditional targets, they are more sensitive to the focus position. The through focus image formed at the image plane depends on the relative focus position between the target and the optical system. An appropriate design for the optical configuration and target geometry produces a unique image at each focus position, for a specific physical feature.

Diarylethene is a reversible photochromic material that can be applied in volume holographic data storage. The optical anisotropy (dichroism and birefringence) of the diarylethene molecule, induced by polarized light illumination, allows the recording of polarization holograms which can multiple two independent holograms in a common volume. In this paper, a new holographic storage scheme with two data channels based on the properties of polarization holograms is proposed. The information of two data-channels can be stored and retrieved simultaneously with negligible inter-channel crosstalk. Thus, the data transfer rate will be possibly doubled.

The binary phase-only filter (BPOF) based watermarking for image authentication was proposed earlier [5] and it shows good performance. In this paper, three image self-authentication algorithms based on BPOF with different watermark embedding methods from Reference 5 are proposed. The BPOF of an image is used as the watermark to embed into its Fourier spectrum by adding to the magnitude or quantizing the magnitude of the Fourier spectrum. For image authentication, either the correlation between the BPOF of the test image with its Fourier magnitude spectrum is computed, or the correlation between the phase information of the test image with the candidate watermark extracted from it is calculated, according to the different embedding methods used in the embedding stage. By using these embedding methods, we expand the potential watermark embedding strength, which is very important for security and robustness of digital watermarking. The performance of these three algorithms is evaluated via computer simulation.

Level set methods have recently been applied to a number of image processing and computer vision applications. However, they have been suffered from the computational complexity. This paper exploits the parallel processing capability of opto-electronic signal processing systems for real-time level-set computation. The most timeconsuming operation in level set methods is the computation of the signed distance function from each grid point to the zero-level set. We show that it can be represented by thresholded correlation operations, and therefore it can be easily realized using an optical correlator. A fast level-set image processing system is constructed based on a joint transform correlation architecture. The simulation results are given.

Compression and encryption/decryption are necessary for secure and effcient storage and transmission of image data. We present an optical encryption technique that takes advantage of both the massive parallelism inherent in optical systems and the flexibility offered by digital electronics. The encryption is performed using a phase mask and Fresnel propagation. We nonuniformly quantize the complex-valued encrypted hologram pixels using an artificial neural network. The in-line digital holograms of three-dimensional objects were created using phase-shift interferometry. With our lossy data compression technique we achieved good quality decryption and reconstruction from objects with a compression ratio of 32.

The new approach for creation of film reflecting holographic marks for optical security is proposed. Such marks are replicas of a reflecting master hologram recorded on a chalcogenide glass layer. To receive the master hologram, the joint power spectrum of an input phase mask or a transformed phase mask and a reference phase mask is produced at the plane of the hologram writing and is modulated by an inclined laser beam. If an inclined laser beam illuminates the replica recorded on a flexible substrate, phase noise including speckle noise is eliminated because the hologram carrier frequency exceeds greatly the limiting frequency of the phase noise power spectrum. Experimental results have shown the principal possibility to produce the high performance film reflecting holographic marks for security applications. The proposed approach can be combined with technologies for fabrication of rainbow holograms. In this case, the received rainbow holograms are the reflecting holographic marks simultaneously. Therefore, they can be verified not only visually, but also by means of automatic identification.

In this paper, we present a Face Recognition method based on the combination of the Gabor Wavelets (GW) and the Phase Congruency (PC) method [1]. While the GW method allows an efficient space-frequency analysis to code the Face Image points, it requires significant down-sampling, in order to end up with a reasonably small-size feature vector. Now, the Phase Congruency method can be used as an efficient features detector, to uncover the salient local features of the face and can be computed using the GW Transform. An additional advantage of the Phase Congruency method is its insensitivity to variations in image illumination and contrast. The method proposed is to use the PC method in determining the salient points of the Face Image, thus replacing the random down-sampling method. The first step in our proposed method is to obtain the local frequency information of a face image using a multi-scale, multi-orientation set of Gabor filters, from which the Phase Congruency image is computed. We then use this method to select a limited number of maximum-value points, whose values are taken from the GW- transformed face images, forming a feature vector of about 5000 components. Preliminary results using the ORL face dataset show 98% recognition rate even without the use of the PCA method. Upon using the PCA method we can further reduce the number of components to 45 while still retaining the recognition rate of 98%. This as compared to a recognition rate of 96% using GW and PCA with a random 64:1 down-sampling on the GW coefficients. The proposed combined method, allows in addition to an efficient reduction in the number of image points used, the derivation of both the PC image and the GW feature vector representation, using a single GW transform.