Recent developments in solid-state image sensors and digital computers have made it possible to directly record holograms by Charge Coupled Device (CCD) camera and numerical reconstruction of the object wave front by computer. Digital holograms recorded with a CCD array are numerically reconstructed in amplitude and phase through calculation of the Fresnel-Kirchhoff integral. Two methods are usually adopted to reconstruct digital holograms called Fresnel Transformation Method (FTM) and the Convolution Method (CM). In FTM, the reconstruction pixel increases with the reconstruction distance so that the size of image, in terms of number of pixels, is reduced for longer distances, limiting the resolution of amplitude and phase reconstruction. In CM, by contrast, the reconstruction pixel does not change, but remains equal to the pixel size of recording array. The CM is more appropriate for reconstruction at small distances whereas the FTM is useful for longer distances according to the paraxial approximation necessary to apply it. The flexibility offered by the reconstruction process in Digital Holography allows exploitation of new possibilities of application in different fields. Through the reconstruction process we will show that it is possible to control image parameters as focus distance, image size and image resolution. Those newly explored potentialities open further novel prospective of application of Digital Holography in single and multi-wavelengths operation either for display and metrological applications. We demonstrate the concept of controlling parameters in image reconstruction of digital holograms in some real situations for inspecting silicon MEMS structures.

We address the use of transmission geometry volume holograms as depth-selective imaging elements in profilometry. We derive the point-spread function (PSF) of the volume holographic imaging system using volume diffraction theory and use the PSF to estimate depth resolution. Experimentally measured PSF and depth-selective images are presented to verify the theoretical predictions. Furthermore, we show that with prior knowledge of the object, depth resolution can be improved greatly with the method of inclined illumination. In more general cases, super resolution can also be achieved with digital post-processing methods such as Viterbi algorithm (VA). We show that computational complexity can be reduced with surface constraints. Resolution improvement by a factor of 5 was obtained in experimental demonstration.

Digital holography is a successful technique for recording and reconstructing three-dimensional (3D) objects. The recent development of megapixel digital sensors with high spatial resolution and high dynamic range has benefited this area. We capture digital holograms (whole Fresnel fields) using phase-shift interferometry and compress then to enhance transmission and storage effciency. Lossy quantization techniques are applied to our complex-valued holograms as the initial stage in the compression procedure. Quantization reduces the number of different real and imaginary values required to describe each hologram. We outline the nonuniform quantization techniques that we have had some success with thus far, and present our latest results with two techniques based on companding and histogram approaches. Companding quantization attempts to combine the effciency of uniform quantization with the improved performance of nonuniform quantization. Our results show that companding techniques can be comparable with k-means and neural network clustering algorithms, while only requiring a single-pass processing step. In addition, we report on a novel lossy compression technique that utilizes histogram data to quantize digital holograms. Here, we use the results of a histogram analysis to inform our decision about the best choice for quantization values.

Conventional integral imaging systems utilize lenslet arrays with fixed focal lengths and aperture sizes. In this paper, we propose a time-multiplexed integral imaging method to enhance both the depth of focus and the resolution of a three-dimensional image by displaying it using an array of lenslets with different focal lengths and aperture sizes. The non-uniform lenslet parameters (focal lengths and aperture sizes) for our method are calculated. Our theoretical analysis indicates that significant improvements in both depth of focus and resolution can be obtained using the proposed technique. To the best of our knowledge, this is a first report on developing integral imaging systems using lenslets with non-uniform focal lengths and aperture sizes.

Structured light pattern projection is a well known method of accurately extracting 3-Dimensional information of a scene. Traditional multi-frame structured light methods require several different patterns to recover the depth, without ambiguity and albedo sensitivity, and are corrupted by object motion during the projection/capture process. The authors have developed a methodology for combining multiple patterns into a single composite pattern by using spatial modulation techniques. A single composite pattern projection does not require synchronization with the camera so the data acquisition rate is only limited by the video rate and therefore suitable for high-speed depth measurement. However, the composite pattern is restrained by the spatial bandwidth directly related to the number of embedded patterns and the lateral resolution of the camera. Another problem is the processing requires image demodulation which is computational intensive. As part of a NASA Phase I STTR, we address the first limitation by analysis of the source of the error and post-processing the reconstruction data with dynamic programming approach. For the second problem we propose the use of a 4-f optical correlator, not as a correlator, but instead as an optical demodulator. Simulation results show reasonable depth reconstruction using our strategy for composite pattern after the post-processing.

We report on the results of a study into the characteristics of the blockwise discrete Fourier transform (DFT) coefficients of digital hologram data, with the aim of efficiently compressing the data. We captured digital holograms (whole Fresnel fields) of three-dimensional (3D) objects using phase-shift interferometry. The complex-valued fields were decomposed into nonoverlapping blocks of 8x8 pixels and transformed with the DFT. The inter-block distributions of the 64 Fourier coefficients were analyzed to determine the relative importance of each coefficient. Through techniques of selectively removing coefficients, or groups of coefficients, we were able to trace the relative importance of coefficients throughout a hologram, and over multiple holograms. We used rms error in the reconstructed image to quantify importance in the DFT domain. We have found that the positions of the most important coefficients are common throughout four of the five digital holograms in our test suite. These results will aid us in our aim of creating a general-purpose DFT quantization table that could be universally applied to digital hologram data of 3D objects as part of a JPEG-style compressor.

We propose and experimentally demonstrate a new reconstruction method of objects hidden in scattering medium. The object (chicken bone) hidden between two slabs of chicken breast is reconstructed from many speckled images formed by a microlens array (MLA). Each microlens from the array projects a small different speckled image of the hidden object onto a CCD camera. The entire noisy images from the array are digitally processed to yield the hidden object. Following this method, a different algorithm implemented on the same optical system has been developed. This modified algorithm, based on the point-source reference method improve the resolution of the previously method. Experimental results are presented that demonstrate our theory and possible applications of this technique are discussed.

Moire fringes appearing in multiview full-parallax 3 dimensional imaging systems can be minimized by proper selection of the vertex angle of pixel cells. Pixel cells with arbitrary vertex angles are built by crossing a pair of discrete line arrays with gradients ± α. The discrete lines are form by the sides of pixels along the straight lines approximating the discrete lines. The gradient of the lines is defined as the ratio between pixel numbers in vertical and horizontal directions. This method allows creating rhomb approximating pixel cells with a desired shape.

We present a method for passive ranging with incoherent light. The scheme uses a single optical channel and is particularly suitable for locating and ranging particles. Our aim is to create an optical system with increased discrimination among depth planes as compared to classical clear aperture solutions. We thus propose a criterion for evaluating a general point spread function for use in passive ranging. Then, we show that rotating point spread functions are good according to this criterion. An experimental realization of the point spread function by use of a computer-generated hologram is presented as well as a simulation of its depth discrimination.

In this paper, a new rectification scheme to transform the uncalibrated stereo image pair into the calibrated one is suggested and its performance is analyzed by applying this scheme to reconstruction of the intermediate views for multi-view stereoscopic display. In the proposed method, feature points are extracted from the stereo image pair through detection of the corners and similarities between each pixel of the stereo image pair. And then, using these detected feature points, moving vectors between the stereo image pair and the epipolar line is extracted. Finally, the input stereo image pair is rectified by matching the extracted epipolar line between the stereo image pair in the horizontal direction. From some experiments on synthesizing the intermediate views by using the calibrated stereo image pairs through the proposed rectification algorithm and the uncalibrated ones for three kinds of stereo image pairs; 'Man', 'Face' and 'Car', it is analyzed that PSNRs of the intermediate views reconstructed from the calibrated images are improved about 2.5 ~ 3.26 dB than those of the uncalibrated ones.

We present a non-mechanical, dynamically programmable, all-optical image rotator, which can rotate an input image to any angle or a grid given by 360°/2ⁿ, where n is the number of stages. The image rotator uses cascaded stages in which each stage rotates the image by an angle given by half the previous stage. Each stage uses an Ferroelectric Liquid Crystal (FLC) polarization switch to select between a straight through path and a deflected path with an odd number of bounces, that when rotated to an angle, operates as an image rotating prism. An FLC is used for each stage to choose the polarization and therefore whether to rotate the image or not. By switching the FLC director orientation by 45 for each stage, images can be rotated to an arbitrary angle at a speed of several KHz.

We propose a novel, wideband spectrum analyzer based on spectral hole burning (SHB) technology. SHB crystals contain rare earth ions doped into a host lattice, and are cooled to cryogenic temperatures to allow sub-MHz hole burning linewidths. The signal spectrum is recorded in an SHB crystal by illuminating the crystal with an optical beam modulated by the RF signal of interest. The signal's spectral components excite those rare earth ions whose resonance frequencies coincide with the spectral component frequencies, engraving the RF spectrum into the crystal's absorption profile. Probing this altered absorption profile with a low power, chirped laser while measuring the transmitted intensity results in a time-domain readout of the accumulated RF signal spectrum. The resolution of the spectrum analyzer is limited only by the homogeneous linewidth of the rare earth ions (< 1 MHz when the SHB crystal is cooled to cryogenic temperatures). The spectrum analyzer bandwidth is limited by the inhomogeneous linewidth and by the electro-optic modulator bandwidth, both of which can be > 20 GHz.

A novel waveguide sensor capable of sensing multiple analytes directly and in real time with label-free, local detection has been investigated. Numerical simulations agree with analytical calculations of the sensor sensitivity. The waveguide parameters including detector to core distance, adlayer length, and surface roughness have been extensively analyzed. Initial experimental realization efforts are summarized.

A microfluidic passive cavity interferometer based biosensor was developed in this work. Polystyrene microspheres were used to test the device performance. Measured transmission spectra of single microspheres were compared to the modeled results.

We report for the first time an electrically pumped vertical cavity surface emitting laser (VCSEL) with a microfluidic channel as an integral part of the laser cavity to form a photonic biosensor. This paper demonstrates the dependence of threshold current and slope efficiency of the laser diode on the refractive index of the fluid in the channel.

In the past decade, Field Programmable Gate Arrays (FPGA) has significantly influenced the landscape of the electronic industry. In particular, in the areas of semiconductor manufacturing, CAD tool designs and a wide range of digital logic applications. Primarily, research efforts in the FPGA community have concentrated on improving the reconfigurability or programmability of present day architecture for digital applications. However, the digital nature of FPGA technologies limits their applicability to a wide range of applications that depend on analog circuitry, photonic and RF based technologies. As with any ASIC design, the turn-around time between design iterations may be several months which is prohibitively long for multi-technology test-bed systems where the system designer depends on a rapid prototyping/experimentation environment that allows for optimization of processing algorithms and system architecture. Therefore, we developed innovative FPGA architecture that merges conventional FPGA technology with mixed signal and other multi-technology device. In this paper we discuss the Multi-Technology-FPGA (MT-FPGA) architecture that allows the user to have flexible rapid prototyping environment and provides him or her with the benefits of a conventional FPGA in a mixed signal domain. We substantiate this concept by implementing this architecture in TSMC 0.35 μm process and discussing the results of a variable threshold optical receiver circuit suitable for photonic information processing.

Recent advances in the integrated electronic circuit industry have spurred efforts to develop technologies that efficiently integrate optics and electronics on a single Complementary Metal Oxide Semiconductor (CMOS) chip. Such CMOS technologies can significantly increase circuit functionality and performance at low fabrication and system cost, thereby accelerating the trend of significant growth in this area. The new functionality could include optical based sensors, image processing, and intelligent optical read heads for faster and more efficient data sorting and searching. The reliability of such monolithic CMOS based functions would be drastically improved relative to their bulk optic counterparts. In the optical telecommunications industry, short haul fiber links would benefit from low cost, silicon CMOS based photoreceivers. One of the primary challenges facing the designers in implementing CMOS based optoelectronic circuits is opto-electrical conversion efficiency. The poor optical responsivity of silicon leads to a bottleneck in the optical to electrical conversion for CMOS based photodetectors. This can be compensated in part through more efficient receiver electronics. Efforts have been made to provide mixed signal circuit design to analyze CMOS based high performance, low noise, integrated receiver circuits. This paper evaluates the performance analysis of five types of photoreceiver configurations that were designed for specific applications.

Certain image processing methods such as filter banks, wavelet packets, and multiresolution analysis have been extensively used for efficiently decomposing, de-noising, compressing and reconstructing images in recent years1. While these methods have been applied primarily in images, their usefulness for decomposing and de-noising sets of measured data has not been thoroughly established yet. This paper will explore the potential of the application of image processing methods in non-image data sets. It is shown that filter banks can be potentially used to process and de-noise seismic data sets successfully. The idea is to treat a seismogram like a "conventional" image and extract certain features in a similar fashion to traditional image processing techniques. In this particular paper, the usage and application of wavelet bases will be explored.

In this paper an automated technique for adaptive radar polarimetric pattern classification is described. The approach is based on a genetic algorithm that uses probabilistic patterns separation distance function and searches for those transmit and receive states of polarization sensing angles that optimize this function. Seven pattern separation distance functions, the Rayleigh quotient, Bhattacharyya, Divergence, Kolmogorov, Matusta, Kullback-Leibler distances, and the Bayesian Probability of Error, are used on real, fully polarimetric synthetic aperture radar target signatures. Each of these signatures is represented as functions of transmit and receive polarization ellipticity angle and the angle of polarization ellipse. The results indicate that based on the majority of the distance functions used; there is a unique set of state of polarization angles whose use will lead to improved classification performance.

One coherent processor and one incoherent processor, both including an active contour optical implementation were constructed and are presented. The coherent processor consists of a complete optical target tracking processor combining a Joint Transform Correlator with an optical implementation of a segmentation method based on active contours or "snakes". The incoherent processor is an optoelectronic multichannel processor that is able to segment an object in a real image. The process is based on an active contour algorithm that has been transposed to optics in order to accelerate image processing. The correlator, in its multichannel version, speeds up the overall frame rate of the optoelectronic processor. Experimental results for both processors are presented.

A time-integrating acousto-optic correlator (TIAOC) is a good candidate for imaging and target detection using a wideband random noise radar system. We have developed such a correlator for a random noise radar with a signal frequency range of 1-2 GHz. This system has demonstrated good wideband signal correlation performance with good dynamic range and fine tuning of delays.

Phase-only spatial light modulators provide active pattern projection. Unlike incoherent techniques, the pattern energy is inversely proportional to the total pattern area. We refer to this flexible pattern/beamsteering system as the real-time adaptive multi-spot laser beamsteering system (RAMS-LBS). The spatial light modulator under investigation is a, 512x512 element, phase-only liquid crystal device recently produced by Boulder Non-linear Systems Incorporated. A laser tweezer is a powerful micromanipulation tool in both the physical and life sciences. In this study, we introduce the detection and tracking of the movement of particles that are controlled by the laser tweezers. The detection and tracking philosophy of these methods are to use optical flow and matched filter techniques. Our discussion will include different tracking protocol and some demonstrations of shape recognition. We have also developed a numerical simulation integrated with experimental implementation.

There has been considerable attention paid in recent literature to the use of optical signal processing in the field of image encryption and security. In most cases this involves the use of optical transforms based on quadratic phase systems (to implement the optical Fourier Transform (FT), the optical fractional Fourier Transform (FRT), the Fresnel transform (FST) and the most general Linear Canonical Transform (LCT). Random phase screens or random shifting.stages are applied after optically transforming to a new domain. The process may be repeated for deeper encryption. Each stage of the encryption process may change the position and spatial extension of the complex distribution on the plane normal to the propagation axis. Each stage may also change the frequency distribution of the signal. Therefore, the space bandwidth product (SBP), which is equal to the number of discrete samples that are required to fully represent our signal, will also change. In general the encrypted image is complex and recording must be carried out using a holographic material or using digital holographic methods. In each case it is desirable to know the spatial extension of the signal to be recorded, its position, and its spatial frequency extension. In this way we can determine which holographic materials will meet the criteria or which cameras will have a suitable number of pixels, greater than or equal to the space bandwidth product, if digital holography is used. We show how the matrices associated with the effect of a LCT on the Wigner Distribution Function (WDF) provide us with an efficient method for finding the position, spatial extent, spatial frequency extent and space bandwidth product of the encrypted signal. We review a number of methods, which have recently been proposed in the literature for the encryption of two-dimensional information using optical systems based on the FT, FRT, FST and LCT. We apply the new matrix technique to some of them.

This paper reports the recent steps to the attainment of a compact high-speed optoelectronic neuroprocessor based on an optical broadcast architecture. The optical broadcast architecture is composed of a set of electronic processing elements that work in parallel and whose input is introduced by means of an optical sequential broadcast interconnection. Because of the special characteristics of the architecture, that exploits electronics for computing and optics for communicating, it is readily scalable in number of neurons and speed. This paper focuses on the improvement of the optoelectronic system and electronic neuron design to increase operation speed with respect to previous prototype.

The Fractional Fourier Transform (FRT) in combination with speckle photography has previously been used to measure surface tilting and translation. Previous Optical Fractional Fourier Transform (OFRT) based techniques used to determine such motion, have not been able to discern the direction of the tilt/translation. A simple new approach involving the use of correlation is presented to overcome this limitation. This is combined with an OFRT system, and controlled variation of the minimum resolution and dynamical range of measurement is demonstrated. It is then confirmed that if a rigid body’s motion is captured using two separate OFRT systems, the direction of both the tilting and in plane translation motion of the body can be determined without apriori knowledge. Experimental results are presented which confirm the validity of theoretical predictions.

We introduce a new method of deriving numerical algorithms for Linear Canonical Transforms (LCT) based on matrices, which act on phase space and distort the shape of the Wigner Distribution Function. Special cases of the LCT include the Fourier Transform (FT), the fractional Fourier Transform (FRT), the Fresnel Transform (FST). We show that many of the existing algorithms, which have been discussed in the literature, can be derived efficiently using this method. They can also be optimised and the relationship between them is discussed. In the case of the FRT all of the existing algorithms can be made index additive and reversible using correct amounts of interpolation and decimation. We derive many new algorithms for the LCT and show the means for deriving many more.

Analogue Optical Signal Processing is a very important area in optics and central to it, is the implementation of the Optical Fourier Transform (OFT). There are many bulk optical arrangements for implementing the OFT however one which is particularly popular is the Scaled Optical Fourier Transform (SOFT) because it offers the user to the ability to change the size or scale of the output Fourier distribution. In this paper we examine the some of the practical limits introduced by the use of a square and circular apertured spherical lens. We examine the phase deviations and provide a simple rule of thumb, which allows the cautious user to avoid some of the worst case errors arising due to diffraction.

This paper presents experimental results demonstrating adaptive beam forming and jammer nulling for phased-array antenna applications using the Broadband Efficient Adaptive Method for True-time-delay Array Processing (BEAMTAP) algorithm. The BEAMTAP algorithm has the advantage of mapping efficiently into an opto-electronic architecture that minimizes the required number of tapped-delay lines and simultaneously allows for the signals to be processed coherently, assuming that phase stabilization has been achieved. The architecture also utilizes a unique polarization-angle, read-write multiplexing system that allows for 45 dB of total jammer suppression at the output. Successful narrowband and broadband adaptive beam forming and jammer nulling results are provided in the worst-case scenario of co-site interference where both the jamming signal's angle of incidence and spectral content overlap with that of the signal of interest.

A complex pupil filter using electrically address twisted nematic LCD spatial light modulators (SLMs) to obtain superresolution along the radial (transverse) direction is presented. The fact that the commercial LCDs can be modeled to obtain amplitude and phase-only SLMs has increased the scope of improving superresolving power dynamically by a suitable combination of both types in an optical system. In general, amplitude-only or phase-only filters result in unwanted increase of side lobe intensity which is disadvantageous for many applications such as microscopy and data storage. The main objective of the complex filter design is to increase the central to side lobe intensity ratio without affecting the size of the central spot. The complex filter performance is optimized for this purpose. The comparison of this filter with that of the conventional pupil filters of both types is shown by simulations. The complex filter is obtained by concatenating amplitude-only and phase-only SLMs in a 4F processor. The SLMs are addressed at video frame rate by a graphic card from the computer. The optimization procedure along with the experimental procedure are described and the results are discussed in this paper.

We have realized optical self-organizing nodes in which nonlinear weighting is enabled by an opt-electronic hybrid circuit based on optical bistability attained simply by coupling a light emitting diode (LED) and a photo diode (PD), which have their own nonlinearity. By connecting each nodes, we have demonstrated a self-organizing link which can build up a signal propagation path autonomously by itself, applying our newly considered adaptive algorithm. This algorithm is based on the fact that the nonlinearity attained by our coupled LED and PD devices can be regarded to be available for a well established nonlinear function which appears in typical adaptive control theory. We have also demonstrated our first fabrication of self-organizing optical network system with seven adaptive nodes. In this scheme, we have intentionally generated a disconnection or a breaking of wire link between certain nodes in the network, and then we have also confirmed that the optimum alternative route can be made autonomously and the transmission recovered. As a consequence, the present optical self-organizing network system can be a step toward a new method for peer-to-peer communications in optical transmission network.

The limitations of straight forward wavelet transformations have been investigated for some time1. In this paper, it is shown that the time-frequency resolution tradeoff may be significantly improved by frequency modulating the mother wavelet. In this way weak signal components may be more efficiently recovered from strong noise. This technique is applied on discrete seismic data sets. In addition to frequency modulating the mother wavelet, it is shown that the quality of the recovered signals may be substantially improved by the application of weights to modify the mean wavelet transform of the data set. The two-dimensional variance and signal-to-noise ratio (SNR) plots will be used in order to achieve this goal. It is also shown that by employing a frequency selective thresholding method, even better results as far as suppressing noise while keeping the signal can be attained.

A near real-time invariant multi-target tracking algorithm based on the fringe-adjusted joint transform correlator (FJTC) technique is proposed for forward looking infra-red (FLIR) image sequences. The proposed FJTC based tracking approach uses a modified synthetic discriminant function (SDF) concept together with an efficient camera motion compensation technique to accommodate the problem of target signature variation due to 3D distortions and noise. The proposed technique can track small objects comprising of only a few pixels and is capable of compensating the high ego-motion of the sensor. The robustness of the proposed technique is demonstrated with computer simulation performed on sequences of real life FLIR imagery taken from an airborne moving platform.

The performance of a target tracking algorithm is directly related to global motion compensation performance, if the imaging sensor systems are not stable. Especially, forward looking infra-red (FLIR) video sequences are detrimentally affected by camera motion since the infrared camera mounted on an airborne platform suffer from abrupt discontinuities in motion. Since this global motion could cause the movement of the target outside the operational limits of the tracking algorithm, each frame in FLIR sequences has to be recovered by motion estimation technique. In this paper, a normalized cross correlation based template matching algorithm has been developed to accurately estimate and compensate the global motion before the application of the tracking algorithm. Then, the automatic target tracking algorithm has been applied using fringe-adjusted joint transform correlator (FJTC) based target detection and tracking technique.

In this paper, a new Hopfield neural network based supervised filtering technique is proposed. The learnable filtering architecture has been developed by modifying the Hopfield network structure using 2D convolution instead of weight-matrix multiplications. This feature offers high speed learning and testing possibility for image feature extraction process. The learning property of the filtering technique is provided by using a recurrent learning algorithm. The proposed technique has been implemented using joint transform correlator. The requirement of non-negative data for optoelectronic implementation is provided by incorporating bias technique to convert the negative data to non-negative data. Simulation results for the proposed technique are reported for feature extraction problems such as edge detection, and vertical line extraction.

An important step in the fingerprint identification system is the extraction of relevant details against distributed complex features. Identification performance is directly related to the enhancement of fingerprint images during or after the enrollment phase. Among the various enhancement algorithms, artificial intelligence based feature extraction techniques are attractive due to their adaptive learning properties. In this paper, we propose a cellular neural network (CNN) based filtering technique due to its ability of parallel processing and generating learnable filtering features. CNN offers high efficient feature extraction and enhancement possibility for fingerprint images. The enhanced fingerprint images are then introduced to joint transform correlator (JTC) architecture to identify unknown fingerprint from the database. Since the fringe-adjusted JTC algorithm has been found to yield significantly better correlation output compared to alternate JTCs, we used it for the identification process. Test results are presented to verify the effectiveness of the proposed algorithm.

Many optical or image processing tasks reduce to the optimization of some set of parameters. Genetic algorithms can optimize these parameters even when the functions they map are fairly complicated, but they can only do so the point where the fitness functions they are given can differentiate between good results and the best result. This can occur when the optimal point is in a region (in a three dimensional example) such as a plateau, where all the surrounding points are of very nearly the same fitness. If there are multiple peaks in close proximity, all of nearly the same fitness but with very deep divides, the algorithm will have trouble 'hopping' from one to the other. One way to overcome these obstacles is to scale the fitness values given by the fitness function, thereby gently modifying the fitness function from the point of view of the algorithm, thus rewarding the more fit solutions to a higher precision than would naturally occur. Four such scaling methods will be compared based upon their handling of a sample set of optical processing data. Success will be determined by comparing the variance over time, selection pressure over time, and best of generation graphs.

A three-dimensional (3D) pattern recognition technique using classical joint transform correlation was proposed recently. However, it exhibits the same drawbacks of classical two-dimensional classical joint transform correlation by producing wide and broad correlation peak in the output plane. Thus, we propose a technique based on fringe-adjusted joint transform correlation to be used in 3D pattern recognition. The proposed technique yields better correlation discrimination ability compared to alternate 3D classical joint transform correlation by producing sharper and stronger correlation peak intensity. Simulation results verify the performance of the proposed technique.

In holographic memory the coherent interference recording is necessary. However, for a good image quality with speckle reduction in the imaging system, partial coherence or incoherence of the light source is desired. In this paper, the influence of coherence properties of the object and reference beams on the characteristics of the images stored and retrieved is discussed. During the recording process, using a vibrating uniform band-limited diffuser, a proper partial coherence is maintained and image detail down to the diffraction limit of the imaging system is preserved. In the readout process, serial pages near the Bragg condition are retrieved for the average processing. These methods are very effective to reduce the speckle noise and to achieve a low raw bit error rate. The coherence length required for holography is also discussed when we choose a compact low-cost laser source.

The biometric feature, iris, has advantages in person identification, such as complex texture, almost unchanged throughout the lifespan. Compared with the famous methods propose by Daugman and Boles, the system of Yong Zhu, et al., not only takes good use of the 2D texture, but also is more robust for using statistic values of the wavelet transformed images as features for recognition. Because wavelet transform is time consuming, a volume holography opto-electronic hybrid system with high parallelism is constructed in this paper. Li Ding, et al., introduced wavelet packet transform into an optical recognition system based on volume holography to reduce the number of images stored in the photo-refractive crystal. By joint best basis selection, eigen-images corresponding to the best wavelet packet bases are generated and stored to replace the reference images. This replacement results in high compression. Theoretical analysis and experimental results both show their scheme achieves significant compression and accurate recognition at the same time. Wavelet packet compression is also utilized in our system. But the best basis selection algorithm is modified. For iris identification, we use the recognition capacity of each wavelet packet basis instead of the entropy because the latter is not for recognition. Furthermore, in the post-processing stage, we use statistic features, like Yong Zhu, to represent each iris pattern which makes the system more robust to the errors caused by optical system. So our system combines the advantages of optics parallelism, high image compression and accuracy of digital processing. Simulation results show a high identification rate is obtained.

The most common sampling theorem is Shannon-Whittaker sampling theorem. While this theorem has been found very useful in many domains, there are cases in which it fails to determine the correct minimal sampling rate. Such a case is encountered in digital holography. It has been previously shown that a sampling rate that is lower than Nyquist rate can be applied in digital holography without loss of information. In this work we develop a generalization of the classical sampling theorem based on an analysis of the sampling process in Wigner domain. The generalized sampling criterion obtained is more widely applicable than Nyquist criterion. In particularly we demonstrate the application of this theorem in digital holography.