A neighborhood-dependent component feature learning method for regression analysis in single-image superresolution is presented. Given a low-resolution input, the method uses a directional Fourier phase feature component to adaptively learn the regression kernel based on local covariance to estimate the high-resolution image. The unique feature of the proposed method is that it uses image features to learn about the local covariance from geometric similarity between the low-resolution image and its high-resolution counterpart. For each patch in the neighborhood, we estimate four directional variances to adapt the interpolated pixels. This gives us edge information and Fourier phase gives features, which are combined to interpolate using kernel regression. In order to compare quantitatively with other state-of-the-art techniques, root-mean-square error and measure mean-square similarity are computed for the example images, and experimental results show that the proposed algorithm outperforms similar techniques available in the literature, especially at higher resolution scales.
Automatic target detection and tracking requires efficient recognition of the target pattern in variable environmental conditions. Optical joint transform correlation (JTC) method has been proven to be efficient in recognizing a target without requiring complex optical set up. However, the classical JTC suffers from poor correlation performance, which can be improved through the use of different and modified designs. A very successful scheme is developed by employing phase-shifted and phase-encoded fringe-adjusted JTC (SPFJTC), which provides with a high discrimination between a target and non-target objects in a given scene and better utilization of the space-bandwidth resource. Further enhancement of the target detection performance can be achieved by incorporating log-polar transform in the SPFJTC technique. We applied the SPFJTC technique to the log-polar transformation of both the reference image and the input scene that makes the pattern recognition invariant to rotation and scale variations. Peak-to-side lobe ratio is measured and a threshold operation is employed to detect and track a target in an unknown input scene.
A novel and robust technique is proposed in this paper for securing confidential information by utilizing
orthogonal coding scheme, encoded steganography and nonlinear encryption through joint transform
correlation. Different biometric signatures are encoded using individual orthogonal codes and then
multiplexed together. The encrypted and multiplexed image is hidden inside a cover image employing a
steganography technique, where one from the three least significant bits is chosen using another secret
key. A color cover image is utilized which is decomposed into three color components, red, green and
blue, so that three different sets of biometric signatures can be embedded into each of the color
components. The color stego image is finally encrypted using multiple phase-shifted reference joint
transform correlation (MRJTC) technique. The proposed encryption technique is a nonlinear process
which increases the security strength significantly against any unauthorized access. The encoded
steganography technique reduces the vulnerability that an intruder can retrieve any information from a
given image through any steganalysis attack. Finally, the orthogonal coding scheme enhances the
robustness by making the biometric information almost inaccessible without authorization.
The objective of this paper is to develop a novel approach for encryption and compression of biometric information
utilizing orthogonal coding and steganography techniques. Multiple biometric signatures are encrypted individually
using orthogonal codes and then multiplexed together to form a single image, which is then embedded in a cover image
using the proposed steganography technique. The proposed technique employs three least significant bits for this purpose
and a secret key is developed to choose one from among these bits to be replaced by the corresponding bit of the
biometric image. The proposed technique offers secure transmission of multiple biometric signatures in an identification
document which will be protected from unauthorized steganalysis attempt.
Optical joint transform correlation (JTC) has been proven to be an efficient pattern recognition tool,
especially, for real-time applications. However, the classical JTC suffers from a lot of limitations such as broad correlation peaks, large side lobes, duplicate correlation peaks and low discrimination
between target and non-target objects. This paper proposes a nonlinear JTC based target detection and tracking technique, where the reference image is phase-shifted and phase-encoded and then fed
to two parallel processing channels. Each channel introduces the unknown input scene and performs Fourier transformations to obtain the joint power spectra signals, which are then combined and
phase-encoded. Then a nonlinear operation is performed on the modified power spectrum followed by the application of fringe-adjusted filtering operation. A subsequent inverse Fourier transform
operation yields the correlation output containing a highly distinct peak corresponding to each target present in the input scene. The reference image phase-encoding process removes any overlapping
issue among the input scene objects, which is a drawback of classical JTC technique. An updated
decision criterion is developed for the correlation plane so that it can accurately identify the location
of the target. The proposed pattern recognition technique offers an excellent alternative for target
tracking in an unknown video sequence.
We have developed a novel face recognition technique utilizing optical joint transform correlation (JTC)
technique which provides with a number of salient features as compared to similar other digital techniques,
including fast operation, simple architecture and capability of updating the reference image in real time. The
proposed technique incorporates a synthetic discriminant function (SDF) of the target face estimated from a
set of different training faces to make the face recognition performance invariant to noise and distortion. The
technique then involves four different phase-shifted versions of the same SDF reference face, which are
individually joint transform correlated with the given input scene with unknown faces and other objects.
Appropriate combination of correlation signals yields a single cross-correlation peak corresponding to each
potential face image. The technique also involves a fringe-adjusted filter to generate a delta-like correlation
peak with high discrimination between the target face and the non-target face and background objects.
Performance of the proposed face recognition technique is investigated through computer simulation where it
is observed to be efficient and successful in different complex environments.
An optical joint transform correlation-based cryptographic system is a used to feed multiple phase-shifted encryption keys into four parallel channels along with a to-be-encrypted signal in the form of an image. The resulting joint power spectra (JPS) signals are phase-shifted and then combined to yield a modified JPS signal. Inverse Fourier transformation of the modified JPS signal yields the secured encrypted image. For decryption purpose, the received encrypted signal is first Fourier transformed and multiplied by the encryption key used in encryption. The derived signal is then inverse Fourier transformed to generate the output signal. The proposed system offers a nonlinear encryption without the involvement of any complex mathematical operation on the encryption key otherwise required in similar encryption techniques and is invariant to noise. Computer simulation results are presented to show the effectiveness of the proposed scheme with binary, as well as gray images in both noise-free and noisy environment.
This paper proposes a new pattern recognition system employing optical joint transform correlation (JTC)
technique which offers a great number of advantages over similar digital techniques, including very fast
operation, simple architecture and capability of updating the reference image in real time. The proposed JTC
technique incorporates a synthetic discriminant function (SDF) of the target image estimated from different
training images to make the pattern recognition performance invariant to noise and distortion. It then involves
four different phase-shifted versions of the same target SDF reference image, which are individually joint
transform correlated with the given input scene. When the correlation signals are combined, it produces a
single cross-correlation peak corresponding to each potential target present in the given input scene. The
proposed technique also includes a fringe-adjusted filter to generate a delta-like correlation peak with high
discrimination between the target and the background noise. The pattern recognition performance is further
enhanced by incorporating the color information of the target objects in the proposed technique. The proposed
technique is investigated using computer simulation where it shows efficient and successful target detection
performance in different complex environments.
A new security system is proposed using optical joint transform correlation technique which employs multiple
phase-shifted reference images. In the proposed technique, the address code is used as the reference image and
fed into four channels after performing phase shifting on them by different amount. The output signals from
each channel are added with the input image to be encrypted for security purpose. Joint power spectra (JPS)
signals can then be derived by applying Fourier transformation, and the resultant signals are phase-shifted and
combined to form a modified JPS signal. Inverse Fourier transformation of the modified JPS signal yields the
encrypted image which is now secure from any unauthorized access and/or loss of information. For decryption
purpose, the received encrypted signal is first Fourier transformed and multiplied by the address code used in
encryption, which is then inverse Fourier transformed to generate the output signal. The proposed technique
does not involve any complex mathematical operation on the address code otherwise required in other security
techniques. The proposed technique requires a simple architecture and operates fast, automatic and is invariant
to noise and distortions. Performance of the proposed scheme is investigated using computer simulation using
binary as well as gray images in both noise-free and noisy conditions.
A new face recognition system is proposed using a nonlinear image enhancement algorithm
incorporated in a synthetic discriminant function based shifted phase-encoded fringe-adjusted joint
transform correlation (SDF-SPFJTC) technique as a preprocessing step. The given input image recorded
from a long distance is improved by using adaptive dynamic range compression and local contrast
enhancement schemes. The Viola-Jones technique is then applied to detect any human face in the scene and
hence correct its size. Finally the SDF-SPFJTC technique yields the recognition of the target face along
with its location. Computer simulation performed on real life scenes shows efficient and successful
recognition performance in varying environmental conditions.
An optoelectronic neural network based detection technique is proposed for multi-class distortion-invariant
pattern recognition. The neural network is utilized in the training stage for a sequence of multi-class binary and
gray level images for supervised learning using shifted phase-encoded joint transform correlator with fringe
adjusted filter in the hidden layer to create composite images that are invariant to distortion. Simulation results
show that the proposed technique is efficient in recognizing targets in variable environmental conditions.
Detection of small vessels is a challenging task for navy, coast guard and port authority for security purposes. Vessel
identification is more complex as compared to other object detection because of its variability in shapes, features and
orientations. Current methods for vessel detection are primarily based on segmentation techniques which are not as
efficient and also require different algorithms for visible and infrared images. In this paper, a new vessel detection
technique is proposed employing anomaly detection. The input intensity image is first converted to feature space using
difference of Gaussian filters. Then a detector filter in the form of Mahalanobis distance is applied to the feature points
to detect anomalies whose characteristics are different from their surroundings. Anomalies are detected as bright spots in
both visible and infrared image. The larger the gray value of the pixels the more anomalous they are to be. The detector
output is then post-processed and a binary image is constructed where the boat edges with strong variance relative to the
background are identified along with few outliers from the background. The resultant image is then clustered to identify
the location of the vessel. The main contribution in this paper is developing an algorithm which can reliably detect small
vessels in visible and infrared images. The proposed method is investigated using real-life vessel images and found to
perform excellent in both visible and infrared images with the same system parameters.
A novel pattern recognition technique is proposed that employs shifted phase-encoded fringe-adjusted joint transform correlation (SPFJTC) for efficient real-time application and synthetic discriminant function for invariance to distortions. The proposed technique produces a single delta-like correlation for a potential target in the input scene, and performs successfully even in a noisy environment. The simple architecture of the proposed technique can be implemented easily on optoelectronics for very high-speed operation. Computer simulation results verify the efficient performance of the technique under different variations of the input scene and the environment.
A new pattern recognition system is proposed using multiple phase-shifted-reference fringe-adjusted joint transform correlation technique. The algorithm involves four different phase-shifted versions of the reference image, which eliminates all unwanted correlation terms and produces a single cross-correlation signal corresponding to each potential target. A fringe-adjusted filter is designed to generate a delta-like correlation peak with high discrimination between the signal and the noise. In addition, the detection performance is made invariant to different spatial distortions by incorporating a synthetic discriminant function, which is created from a set of training images of the reference object. The target detection system is also designed for recognition of multiple targets belonging to multiple reference objects simultaneously in the given input scene and hence provides a real-time class-associative decision on the presence of any target. The proposed technique is investigated using computer simulation with binary as well as gray images in various complex environments where it performs excellent in every case.
Edge detection is the primary step in image segmentation and target detection applications.
The edge operators proposed so far in the literature, namely, Canny, Sobel, Prewitt, provide a
number of unwanted edges which complicate the foreground object detection process. In this
paper, a novel technique is proposed for edge detection and foreground segmentation
employing two mean filters of different window sizes. A ratio of the filtered images is taken
and normalized. Then a threshold is applied on the histogram of the resultant image to derive
the final output which can detect the edges and hence separate the foreground from the
background. Performance of the proposed method has been investigated through computer
simulation and compared with other existing edge detection techniques using complex reallife
image sequences, which verifies that the technique provides better detection results for
any input scene.
We propose a novel optical pattern recognition system using multiple phase-shifted-reference fringe-adjusted joint transform correlation (MRFJTC) techniques. The MRFJTC algorithm can efficiently detect an object of interest in the input scene by producing a highly distinctive correlation peak while rejecting any and all nontarget objects in a complex background. The simple architecture of the proposed system can simultaneously recognize multiple targets of the reference class when present. The recognition performance is fast, automatic, and invariant to noise and distortions.
KEYWORDS: Multiplexing, Computer security, Image encryption, Binary data, Computer programming, Signal to noise ratio, Information security, Signal processing, Data storage, Computing systems
A novel information security system is developed, employing quadrature multiplexing, to be implemented using optoelectronic devices. Two information signals are encrypted using the same code but two orthogonal functions, and then they are multiplexed together in the same domain. With orthogonal functions having zero cross-correlation between them, the encrypted information remains unaffected. Each encryption and multiplexing process can accommodate two information signals for a single code and hence for a single storage cell or transmission channel. The same process can be performed in multiple steps to increase the multiplexing capability of the system. The proposed security system can enhance the storage capacity and/or maximize the utilization of the available transmission bandwidth. For decryption, the composite encoded signal is correlated using the appropriate code and function. Computer simulation results show that the proposed security system is capable of dealing with both binary and gray-level images with the encrypted images remaining secure.
Pattern recognition for real-time applications requires the detection scheme be a simple architecture, fast in
operation, able to detect all the potential targets without generating any false alarms, and invariant to noise and
distortion. Though several target detection algorithms have been proposed in the literature over the years, but
most of them are found to be not as efficient in meeting all the above-mentioned objective requirements. A new
Gaussian-filtered, shifted phase-encoded fringe-adjusted joint transform correlation technique has been
developed in this paper for an optical pattern recognition system. The input noisy image is first filtered by using
a Gaussian filter, which helps in overcoming the effect of background noise and distortions. Then the filtered
image is correlated with the reference image using the proposed joint transform correlator, which eliminates the
problems of duplicate correlation heights, false alarms and low discrimination ratio. The architecture involves
optical devices including lenses and spatial light modulators, which guarantees the very fast operation required
for real-time applications. Computer simulation results show that the algorithm can successfully discriminate
between targets and non-targets contained in the input scene even in the presence of noise and can also make the
best utilization of the correlation space.
Pattern recognition in hyperspectral imagery often suffers from a number of limitations, which includes
computation complexity, false alarms and missing targets. The major reason behind these problems is that the
spectra obtained by hyperspectral sensors do not produce a deterministic signature, because the spectra
observed from samples of the same material may vary due to variations in the material surface, atmospheric
conditions and other related reasons. In addition, the presence of noise in the input scene may complicate the
situation further. Therefore, the main objective of pattern recognition in hyperspectral imagery is to maximize
the probability of detection and at the same time minimize the probability of generating false alarms. Though
several detection algorithms have been proposed in the literature, but most of them are observed to be
inefficient in meeting the objective requirement mentioned above. This paper presents a novel detection
algorithm which is fast and simple in architecture. The algorithm involves a Gaussian filter to process the
target signature as well as the unknown signature from the input scene. A post-processing step is also included
after performing correlation to detect the target pixels. Computer simulation results show that the algorithm
can successfully detect all the targets present in the input scene without any significant false alarm.
A new technique is proposed for optical encryption and multiplexing of binary characters and images used for personal identification information. Different binary images can first be encrypted using orthogonal code and then multiplexed together in the spatial domain. The resulting encrypted single image provides security as well as makes efficient use of storage and/or transmission capacity. The image can finally be decrypted and the individual input images can be decoded employing the same orthogonal code set. Because of the orthogonal nature of the code used, the encryption and decryption processes do not deteriorate the quality of the images employed. Also, the proposed technique involves a very simple architecture, as it does not require any mathematical transformation.
Optical security systems have attracted much research interest recently for information security and fraud
deterrent applications. A number of encryption techniques have been proposed in the literature, which
includes double random-phase encryption, polarization encoding, encryption and verification using a
multiplexed minimum average correlation energy phase-encrypted filter. Most of these reports employ a
pseudo-random code for each information to be encrypted, where it requires individual storage capacity or
transmission channel for further processing of each information. The objective of this paper is to develop
an optical encryption system employing quadrature multiplexing to enhance the storage/transmission
capacity of the system. Two information signals are encrypted using the same code but employing two
orthogonal functions and then they are multiplexed together in the same domain. As the orthogonal
functions have zero cross-correlation between them, so the encrypted information are expected to be
unaffected by each other. Each encryption and multiplexing process can accommodate two information
signals for a single code and a single storage cell or transmission channel. The same process can be
performed in multiple steps to increase the multiplexing capability of the system. For decryption purpose,
the composite encoded signal is correlated using the appropriate code and the appropriate function. The
proposed technique has been found to work excellent in computer simulation with binary as well as gray
level images. It has also been verified that the encrypted images remain secure, because no unwanted
reproduction is possible without having the appropriate code and function.
A new shifted phase-encoded fringe-adjusted joint transform correlation (SPJTC) technique is proposed for class-associative color pattern recognition. In this technique, the joint color image containing the class member images and unknown input scene images is split into three fundamental color components—red, green, and blue—which are then processed through three different channels using the SPJTC technique to obtain individual joint power spectra (JPS). For correlation performance improvement, a new class-associative color fringe-adjusted filter (CCFAF) has been proposed. The combined JPSs obtained by fusing all of the individual joint power spectra are then multiplied by the CCFAF transfer function. The proposed scheme provides a single correlation peak per target with excellent correlation discrimination for both noise-free and noisy conditions. Simulation results are provided to verify the effectiveness of the proposed technique.
Optical information processing techniques have been developed for information security and fraud deterrent applications. Several encryption methods have been proposed in the literature, which includes optical double random-phase encryption, polarization encoding, encryption and verification using a multiplexed minimum average correlation energy phase-encrypted filter. All these reports employed a pseudo-random number for the code. But as such numbers are not uncorrelated, the security is not guaranteed because a wrong code may also extract some of the features of the coded information. The objective of the paper is to develop an optical security system employing orthogonal code for protection of personal identification information. As the orthogonal codes have zero or minimum cross-correlation depending on the offset between the codes, a wrong code can not decrypt any information. Here a simple encryption technique is proposed in spatial domain, where the input images are first spread in one dimension using an optical lens and then multiplied by the respective code. Finally, the individual encrypted images are superimposed on a common spatial domain. The individual images can then be decrypted by correlating the received signal with the respective address code. Computer simulation results show that any information containing binary characters can be encrypted and then decrypted successfully. The encrypted images are found to be secure, because no unwanted reproduction is possible without having the appropriate code. The technique also offers an efficient use of the storage or transmission capacity. Therefore, the proposed optical encryption technique can be applied to securing personal identification or similar information.
Color pattern recognition techniques involve the separation of basic color components, red, green and blue, by using color filters. Although several joint transform correlation architectures have been proposed in literature for color pattern recognition, however, these algorithms are suitable for single color target detection only and most of them are sensitive to noise and do not efficiently utilizes the space bandwidth product. A new shifted phase-encoded fringe-adjusted joint transform correlation (SPJTC) technique has been proposed in this paper for class-associative color pattern recognition. The color images are first split into three fundamental color components and the individual components are then processed simultaneously through three different channels. The SPJTC technique for each color component again involves two channels, one with the reference image and the other with 180° phase-shifted reference image. Both are phase masked using a random phase and then used with the input scene. The joint power spectra (JPS) are again phase masked and subtracted one from the other. The resultant JPS yields the desired correlation after inverse Fourier transformation. A modified class-associative color fringe adjusted filter is developed for providing single and sharp correlation peak per target while satisfying the equal correlation peak criterion for each class member. The salient feature of the proposed scheme is that the number of channels and processing steps remains constant irrespective of the number of members in the class. Computer simulation verifies the effectiveness of the proposed technique for color images both in binary and gray levels even in presence of noise.
A modified class associative fringe-adjusted filter-based technique is proposed for multiple target detection, where the number of processing steps remains fixed irrespective of the number of objects in the class. An enhanced version of generalized fringe-adjusted filters is developed for correlation improvement. Again, a shifted phase encoding technique is employed for generation of a single correlation peak per target object. The effectiveness of the proposed technique is verified by computer simulation for binary as well as gray-level images both with and without noise.
We investigate the performance of wavelength shift keying (WSK) technique and repeated unequal channel spacing (RUS) scheme and compare them considering a repeaterless optical wavelength-division-multiplexed (WDM) transmission system in the context of four-wave mixing (FWM) effect. The WSK-WDM system outperforms the RUS-WDM system within particular signal levels and enables higher allowable input power, lower power penalty, and higher transmission distance for a given bit error rate at the expense of increased bandwidth. The comparative performance provides important design considerations for a long-haul optical WDM system.
An extensive investigation has been carried out, by computer simulation, to evaluate the impact of self phase modulation (SPM) on residual dispersion for a wavelength-division multiplexed (WDM) system at a bit rate of 10 Gbit/s. Degradation of the eye opening of the transmitted pulses at the output of the transmission fiber due to interplay of the SPM and the group-velocity dispersion effects is investigated for post- and bi-end compensation configurations, including residual dispersion. Hence the eye-opening penalty and the threshold power limit at 3-dB eye-opening penalty are determined for both the configurations. It is found that the bi-end compensation configuration offers the best performance in respect of the SPM effect and that for a WDM system positive residual dispersion should be used.
A distortion-invariant class-associative pattern recognition technique is proposed, where a class of objects may be defined as a group of objects with similarity and dissimilarity among them. The fractional power fringe-adjusted joint transform correlation technique as well as the synthetic discriminant function concept has been effectively utilized to achieve the distortion-invariant detection of multiple dissimilar targets simultaneously present in the input scene. Simulation results prove that the proposed scheme is an effective tool for the detection of multiple dissimilar targets in both binary and gray-level input scenes corrupted by distortion and noise.
Class-associative detection involves recognition of multiple dissimilar targets simultaneously present in the input scene. In this paper, synthetic discriminant function (SDF) has been incorporated in the fringe-adjusted joint transform correlation based class-associative target detection technique to make it distortion invariant. The concept of fractional power fringe-adjusted joint transform correlation (FPFJTC) has been utilized both to generate the SDF based reference images and to detect the class-associative targets using multi-target detection algorithm. FPFJTC provides mainly three different types of filters, may be termed as generalized fringe-adjusted filters (GFAF), to modify the joint power spectrum and thus facilitates the selection of appropriate filter/filters. Here we have proposed the phase-only filter variation from the GFAF at all steps for successful detection. Simulation results verify that the proposed scheme performs satisfactorily in detecting both binary and gray level images of a class irrespective of distortion.
A modified phase-encoded fringe-adjusted joint transform correlation technique is proposed for multiple target detection, where two joint power spectrums (JPS) are formulated utilizing a random phase mask and phase shifted random phase mask to the reference image separately. The final JPS is the difference between the phase encoded and shifted phase encoded JPS which is multiplied by the phase mask before applying the inverse Fourier transform to yield the correlation output. This technique ensures better utilization of the input/output plane space bandwidth product by yielding one delta function like correlation peak for each desired target object and no peak for non-target objects. The proposed technique can effectively detect any number of targets from noise free or noisy input scenes without changing the system parameters and without any degradation of performance. Computer simulation results verify the performance of the proposed technique.
The measurement and evaluation of power spectrum of a semiconductor laser by delayed self-heterodyne interferometer is demonstrated with the use of a short delay fiber. The measured spectrum is analyzed numerically including the effect of a delay time much less than the laser coherence time. The theoretical formulation developed here is found to be found to be accurate since it exhibits a peak with finite width at the center frequency of the measured lineshape. The white and 1/f components of the laser FM noise are then separated successfully by fitting numerical analysis to the experimental results.
Origin of erbium luminescence at 1.54 micrometers , a prospective optical source in silicon based optoelectronics has been analyzed. Erbium atoms in silicon have been considered as recombination centers with specific values of capture and emission coefficients. Electron-hole recombination through these levels has been considered to be the origin of erbium excitation. At steady state of excitation, a certain fraction of erbium sites were found to remain occupied by electrons. Trapped electrons, which eventually recombine with holes in the valence band, provide the energy for (formula available in paper)yields (formula available in paper) transition of erbium atoms. It was however found that, even with 100 percent quantum efficiency of this energy transmission, not every electron- hole recombination corresponds to the excitation of an erbium atom. This wastage of recombination energy was attributed to the rather long lifetime of erbium decay. Capture and emission processes of photo generated excess carriers in the erbium related level have been equated for non-steady conditions. It has been shown that the steady state erbium luminescence actually follows a transient rise, typically of the order of few hundred microseconds. The anomalous behavior of continuous rise of erbium luminescence after termination of short excitation pulses of 30 μs microsecond has been explained mathematically for the first time.
The effect of fiber chromatic dispersion on the performance of a multichannel optical coherent CPFSK system is analyzed including also the effects of shot and thermal noises and crosstalk interference. The sensitivity penalty is found to increase due to waveform distortion caused by chromatic dispersion. The channel frequency separation is, therefore, required to increase to overcome the dispersion effect. The channel spacing requirements become worse with increase in intermediate frequency (IF) and IF bandwidth.
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