Signal-level image fusion has in recent years established itself as a useful tool for dealing with vast amounts of image data obtained by disparate sensors. In many modem multisensor systems, fusion algorithms signifi...
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ISBN:
(纸本)0819449598
Signal-level image fusion has in recent years established itself as a useful tool for dealing with vast amounts of image data obtained by disparate sensors. In many modem multisensor systems, fusion algorithms significantly reduce the amount of raw data that needs to be presented or processed without loss of information content as well as provide an effective way of information integration. One of the most useful and widespread applications of signal-level image fusion is for display purposes. Fused images provide the observer with a more reliable and more complete representation of the scene than would be obtained through single sensor display configurations. In recent years, a plethora of algorithms that deal with the problem of fusion for display has been proposed. However, almost all are based on relatively basic processing techniques and do not consider information from higher levels of abstraction. As some recent studies have shown this does not always satisfy the complex demands of a human observer and a more subjectively meaningful approach is required. This paper presents a fusion framework based on the idea that subjectively relevant fusion could be achieved if information at higher levels of abstraction such as image edges and image segment boundaries are used to guide the basic signal-level fusion process. Fusion of processed, higher level information to form a blueprint for fusion at signal level and fusion of information from multiple levels of extraction into a single fusion engine are both considered. When tested on two conventional signal-level fusion methodologies, such multi-level fusion structures eliminated undesirable effects such as fusion artefacts and loss of visually vital information that compromise their usefulness. images produced by inclusion of multi-level information in the fusion process are clearer and of generally better quality than those obtained through conventional low-level fusion. This is verified through subjective evaluatio
For arbitrary distribution of the additive interference at the communication receiver, we propose a new approach for the signal estimation/detection problems in the FIR channel. By applying the Bayesian law, the MAP e...
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This paper proposes two techniques for low-complexity rate-distortion (R-D) optimized streaming of packetized video. These techniques enable computing packet transmission schedules which satisfy a constraint on the av...
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On the basis of the dichromatic reflection model, recent specular highlight removal techniques typically estimate and cluster illumination chromaticity values to separate diffuse and specular reflection components fro...
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ISBN:
(纸本)9781538692646
On the basis of the dichromatic reflection model, recent specular highlight removal techniques typically estimate and cluster illumination chromaticity values to separate diffuse and specular reflection components from a single image. While these techniques are able to obtain visually pleasing results, their clustering algorithms suffer from bad initialization or are too costly to be computed in real time. In this paper, we propose a high-quality pixel clustering approach that allows the removal of specular highlights from a single image in real time. We follow previous work and estimate the minimum and maximum chromaticity values for every pixel. Then, we analyze the distribution pattern of those values in a minimum-maximum chromaticity space to propose an efficient pixel clustering approach. Afterwards, we estimate an intensity ratio for each cluster in order to separate diffuse and specular components. Finally, we present optimization strategies to implement our approach efficiently for both CPU and GPU architectures. Experimental results evaluated in the available dataset show that the proposed approach is not only more accurate, but is also two times faster than the state-ofthe-art when running solely on the CPU. Running on the GPU, we show that our approach requires approximate to 24 milliseconds to remove specular highlights in an image with 3840 x 2160 (4k) resolution. That makes our GPU implementation more than one order of magnitude (20 x) faster than the state-of-the-art for 4k resolution images, while providing the desired effect accurately.
In recent years, active research has mainly concentrated on authenticating a signature;tracking a document in a digital library, and tamper detection of a scanned document or secured communication using binary images....
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ISBN:
(纸本)0819462918
In recent years, active research has mainly concentrated on authenticating a signature;tracking a document in a digital library, and tamper detection of a scanned document or secured communication using binary images. Binary image steganographical systems provide a solution for the above discussed issues. The two color constraint of the image limits the extension of various LSB embedding techniques to the binary case. In this paper, we present a new data hiding system for binary images and scanned documents. The system initially identifies embeddable blocks and enforces specific block statistics to hide sensitive information. The distribution of the flippable pixels in these blocks is highly uneven over the image. A variable block embedding threshold is employed for capitalizing on this uneven distribution of pixels. In addition, we also present a measure to find the best the cover given a specific file of sensitive information. The simulation was performed over 50 various binary images such the scanned documents, cartoons, threshold color images. Simulation results shows that 1), The amount of data embedded is comparatively higher than the existing algorithms (such as K.H. Hwang et. al [5], J. Chen et. al [10], M Y. WR et. al [9]). 2) The visual distortion in cover image is minimal when compared with the existing algorithms (such as J Chen[10], M Y. Wu *** [9]) will be presented.
The three-volume set CCIS 761, CCIS 762, and CCIS 763 constitutes the thoroughly refereed proceedings of the International conference on Life System Modeling and Simulation, LSMS 2017, and of the International Confere...
ISBN:
(数字)9789811063732
ISBN:
(纸本)9789811063725
The three-volume set CCIS 761, CCIS 762, and CCIS 763 constitutes the thoroughly refereed proceedings of the International conference on Life System Modeling and Simulation, LSMS 2017, and of the International conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2017, held in Nanjing, China, in September 2017. The 208 revised full papers presented were carefully reviewed and selected from over 625 submissions. The papers of this volume are organized in topical sections on: Biomedical Signal processing; Computational Methods in Organism Modeling; Medical Apparatus and Clinical Applications; Bionics Control Methods, algorithms and Apparatus; Modeling and Simulation of Life systems; Data Driven Analysis; image and Video processing; Advanced Fuzzy and Neural Network Theory and algorithms; Advanced Evolutionary Methods and Applications; Advanced Machine Learning Methods and Applications; Intelligent Modeling, Monitoring, and Control of Complex Nonlinear systems; Advanced Methods for Networked systems; Control and Analysis of Transportation systems; Advanced Sliding Mode Control and Applications; Advanced Analysis of New Materials and Devices; Computational Intelligence in Utilization of Clean and Renewable Energy Resources; Intelligent Methods for Energy Saving and Pollution Reduction; Intelligent Methods in Developing Electric Vehicles, Engines and Equipment; Intelligent Computing and Control in Power systems; Modeling, Simulation and Control in Smart Grid and Microgrid; Optimization Methods; Computational Methods for Sustainable Environment.
The proceedings contains 177 papers from the 1997 IEEE International conference on systems, Man and Cybernetics. Topics discussed include: dynamical systems;artificial neural networks;systems stability maintenance;cha...
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The proceedings contains 177 papers from the 1997 IEEE International conference on systems, Man and Cybernetics. Topics discussed include: dynamical systems;artificial neural networks;systems stability maintenance;chaos methods;knowledge extraction;pattern recognition and classification;intelligent control methods;adaptive critics;intelligent information systems;human computer interaction;complex systems;aviation systems;imageprocessing and noise reduction;fuzzy logic controllers;time Petri net models;robotics;manipulators;energy and transportation systems;systems modeling, analysis and evaluation;evolutionary and genetic algorithms;multicriteria decision making;pattern recognition and classification;and computer vision.
Enhancement of degraded images of binary shapes is an important task in many imageprocessing applications, e. g. to provide appropriate image quality for optical character recognition. Although many image restoration...
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ISBN:
(纸本)9783319028958;9783319028941
Enhancement of degraded images of binary shapes is an important task in many imageprocessing applications, e. g. to provide appropriate image quality for optical character recognition. Although many image restoration methods can be found in the literature, most of them are developed for grayscale images. In this paper we propose a novel binary image restoration algorithm. As a first step, it restores the projections of the shape using 1-dimensional deconvolution, then reconstructs the image from these projections using a discrete tomography technique. The method does not require any parameter setting or prior knowledge like an estimation of the signal-to-noise ratio. Numerical experiments on a synthetic dataset show that the proposed algorithm is robust to the level of the noise. The efficiency of the method has also been demonstrated on real out-of-focus alphanumeric images.
In recent years, there has been a growing interest in the development of in vitro models to predict cellular behavior within living organisms. Mathematical models, based on differential equations and associated numeri...
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Stereo-camera systems enjoy wide popularity since they provide more restrictive constraints for 3d-reconstruction. Given an image sequence taken by parallel stereo cameras, a low-rank constraint is derived on the meas...
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ISBN:
(纸本)9783642406010;9783642406027
Stereo-camera systems enjoy wide popularity since they provide more restrictive constraints for 3d-reconstruction. Given an image sequence taken by parallel stereo cameras, a low-rank constraint is derived on the measurement data. Correspondences between left and right images are not necessary yet reduce the number of optimization parameters. Conversely, traditional algorithms for stereo factorization require all feature points in both images to be matched, otherwise left and right image streams need be factorized independently. The performance of the proposed algorithm will be evaluated on synthetic data as well as two real image applications.
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