One of the main challenges of any control (or imageprocessing) paradigm is being able to handle complex systems under unforeseen uncertainties. A system may be called complex here if its dimension (order) is too high...
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ISBN:
(纸本)0819441856
One of the main challenges of any control (or imageprocessing) paradigm is being able to handle complex systems under unforeseen uncertainties. A system may be called complex here if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is uncertain such that classical techniques cannot easily handle the problem. Examples of complex systems are power networks, space robotic colonies, national air traffic control system, an integrated manufacturing plant the Hubble Telescope, the International Space Station, etc. Soft computing, a consortia of methodologies such as fuzzy logic, neuro-computing, genetic algorithms and genetic programming, has proven to be powerful tools for adding autonomy and semi-autonomy to many complex systems. For such systems the size of soft computing control architecture will be nearly infinite. In this paper new paradigms using soft computing approaches are utilized to design autonomous controllers and image enhancers for a number of application areas. These applications are satellite array formations for synthetic aperture radar interferometry (InSAR) and enhancement of analog and digital images.
Genetic algorithms (GAs) are known to be robust for search and optimization problems. image registration can take advantage of the robustness of GAs in finding best transformation between two images, of the same locat...
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Genetic algorithms (GAs) are known to be robust for search and optimization problems. image registration can take advantage of the robustness of GAs in finding best transformation between two images, of the same location with slightly different orientation, produced by moving spaceborne remote sensing instruments. In this paper, we present 2-phase sequential and coarse-grained parallel image registration algorithms using GAs as optimization mechanism. In its first phase, the algorithm finds a small set of goad solutions using low-resolution versions of the images. Based on these candidate low-resolution solutions, the algorithm uses the full resolution image data to refine the final registration results in the second phase. Experimental results are presented and revealed that our algorithms yield very accurate registration results for LandSat Thematic Mapper images, and the parallel algorithm scales quite well on the Beowulf parallel cluster. (C) 2001 Elsevier Science B.v. All rights reserved.
We propose a method of synthesizing computer-generated holograms of real-life three-dimensional (3-D) objects. An ordinary digital camera illuminated by incoherent white light records several projections of the 3-D ob...
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ISBN:
(纸本)0819441856
We propose a method of synthesizing computer-generated holograms of real-life three-dimensional (3-D) objects. An ordinary digital camera illuminated by incoherent white light records several projections of the 3-D object from different points of view. The recorded data are numerically processed to yield a two-dimensional complex function, which is then encoded as a computer-generated hologram. When this hologram is illuminated by a plane wave, a 3-D real image of the object is reconstructed.
A new three-dimensional display system based on a volume-scanning method is demonstrated. To form a three-dimensional real image, an inclined two-dimensional image is rapidly moved with a mirror scanner while the cros...
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ISBN:
(纸本)0819441856
A new three-dimensional display system based on a volume-scanning method is demonstrated. To form a three-dimensional real image, an inclined two-dimensional image is rapidly moved with a mirror scanner while the cross-section patterns of a three-dimensional object are displayed sequentially. A vector-scan CRT display unit is used to obtain a high-resolution image. An optical scanning system is constructed with concave mirrors and a galvanometer mirror. It is confirmed that three-dimensional images, formed by the experimental system, satisfy all the criteria for human stereoscopic vision.
This paper reviews the role of information theory in characterizing the fundamental limits of watermarking systems and in guiding the development of optimal watermark embedding algorithms and optimal attacks. Watermar...
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This paper reviews the role of information theory in characterizing the fundamental limits of watermarking systems and in guiding the development of optimal watermark embedding algorithms and optimal attacks. Watermarking can be viewed as a communication problem with side information (in the form of the host signal and/or a cryptographic key) available at the encoder and the decoder. The problem is mathematically defined by distortion constraints, by statistical models for the host signal, and by the information available in the game between the information hider, the attacker, and the decoder. In particular, information theory explains why the performance of watermark decoders that do not have access to the host signal may surprisingly be as good as the performance of decoders that know the host signal. The theory is illustrated with several examples, including an application to image watermarking. Capacity expressions are derived under a parallel-Gaussian model for the host-image source. Sparsity is the single most important property of the source that determines capacity. (C) 2001 Elsevier Science B.v. All rights reserved.
In this paper, we focus on the total-system-energy minimization of a wireless image transmission system including both digital and analog components. Traditionally, digital power consumption has been ignored in system...
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In this paper, we focus on the total-system-energy minimization of a wireless image transmission system including both digital and analog components. Traditionally, digital power consumption has been ignored in system design, since transmit power has been the most significant component. However, as we move to an era of pico-cell environments and as more complex signal processingalgorithms are being used at higher data rates, the digital power consumption of these systems becomes an issue. We present an energy-optimized image transmission system for indoor wireless applications which exploits the variabilities in the image data and the wireless multipath channel by employing dynamic algorithm transformations and joint source-channel coding. The variability in the image data is characterized by the rate-distortion curve, and the variability in the channel characteristics is characterized by the path-loss and impulse response of the channel. The system hardware configuration space is characterized by the error-correction capability of the channel encoder/decoder, number of powered-up fingers in the RAKE receiver, and transmit power of the power amplifier. An optimization algorithm is utilized to obtain energy-optimal configurations subject to end-to-end performance constraints. The proposed design is tested over QCIF images, IMT-2000 channels and 0.18 mum, 2.5 v CMOS technology parameters. Simulation results over various images, various distances, two different channels, and two different rates show that the average energy savings in utilizing a total-system-energy minimization over a fixed system (designed for the worst image, the worst channel and the maximum distance) are 53.6% and 67.3%, respectively, for short-range (under 20 m) and long-range (over 20 m) systems.
Correlation filters are ideally suited for recognizing patterns in three-dimensional (3D) data. Whereas most model-based techniques tend to measure the overall dimensions of objects and their larger features, correlat...
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ISBN:
(纸本)0819441856
Correlation filters are ideally suited for recognizing patterns in three-dimensional (3D) data. Whereas most model-based techniques tend to measure the overall dimensions of objects and their larger features, correlation filters can readily (and efficiently) exploit intricate surface details, the gray values of surfaces as well as internal structure, if any. Thus correlation filters may be the preferred approach in scenarios when intensity and range data are both available, or when the internal structure of an object has been mapped (e.g. tomography). In this paper, we outline the development of filters for 3D data that we refer to as volume Correlation Filters (vCFs), illustrate their use with range images of an object, and outline future work for the development of 3D correlation techniques.
A digital holographic data reconstruction method with data compression is proposed. We show the number of quantization level of a digital hologram can be reduced. By computer simulations it is confirmed that the metho...
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ISBN:
(纸本)0819441856
A digital holographic data reconstruction method with data compression is proposed. We show the number of quantization level of a digital hologram can be reduced. By computer simulations it is confirmed that the method is especially useful for binary images. For gray scale images, we propose a bit plane decomposition method. By this method, we show both high reconstructed image quality and a high compression ratio can be achieved. This method is applicable to both a normal digital hologram and an encrypted digital hologram.
A Toeplitz-block-Toeplitz (TBT) matrix is block Toeplitz with Toeplitz blocks. TBT systems of equations arise in 2-D interpolation, 2-D linear prediction and 2-D least-squares deconvolution problems. Although the doub...
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ISBN:
(纸本)0780370414
A Toeplitz-block-Toeplitz (TBT) matrix is block Toeplitz with Toeplitz blocks. TBT systems of equations arise in 2-D interpolation, 2-D linear prediction and 2-D least-squares deconvolution problems. Although the doubly Toeplitz structure should be exploitable in a fast algorithm, existing fast algorithms only exploit the block Toeplitz structure, not the Toeplitz structure of the blocks. Iterative algorithms can employ the 2-D FFT, but usually take thousands of iterations to converge. We develop a new fast algorithm that assumes a smoothness constraint (described in the text) on the matrix entries. For an M-2 X M-2 TBT matrix with M M x M Toeplitz blocks along each edge, the algorithm requires only O(6M(3)) operations to solve an M-2 X M-2 linear system of equations;parallel computing on 2M processors can be performed on the algorithm as given. Two examples show the operation and performance of the algorithm.
In this paper, we describe a novel approach to image sequence Segmentation and its real-time implementation. This approach uses the 3D structure tensor to produce a more robust frame difference signal and uses curve e...
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ISBN:
(纸本)0819439819
In this paper, we describe a novel approach to image sequence Segmentation and its real-time implementation. This approach uses the 3D structure tensor to produce a more robust frame difference signal and uses curve evolution to extract whole (moving) objects. Our algorithm is implemented on a standard PC running the Windows operating system with video capture from a USB camera that is a standard Windows video capture device. Using the Windows standard video I/O functionalities, our segmentation software is highly portable and easy to maintain and upgrade. In its current implementation on a Pentium 400, the system can perform segmentation at 5 frames/sec with a frame resolution of 160 x 120.
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