wavelet techniques can be successfully applied in various signal and imageprocessingapplications, namely in image de-noising, segmentation, classification, motion estimation and copy right protection. The proliferat...
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ISBN:
(纸本)9781424429622
wavelet techniques can be successfully applied in various signal and imageprocessingapplications, namely in image de-noising, segmentation, classification, motion estimation and copy right protection. The proliferation of digitized media due to the rapid growth of networked multimedia systems has created an urgent need for copyright enforcement technologies that can protect copyright ownership of multimedia objects. Digital image watermarking is one such technology that has been developed to protect digital images from illegal manipulations. In this paper, a robust and imperceptible watermarking scheme for copy right protection is proposed. The method is based on decomposing an image using the Discrete wavelet Transform, and then embedding locations are generated from the low frequency sub-band by using secrete sort to improve the embedding intensity. From the experimental results, the proposed scheme provides not only good quality, but also good robustness against external attacks, such as rotation, compression, cropping, noise and scaling.
This paper explores the use of satellite images as a valuable source of information to assess the operating conditions of a transportation system after a major disaster that makes traffic information unavailable due t...
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ISBN:
(纸本)9780976348641
This paper explores the use of satellite images as a valuable source of information to assess the operating conditions of a transportation system after a major disaster that makes traffic information unavailable due to loss of power or other damages to the infrastructure. Three methods, namely wavelet transformation analysis, Fourier transformation analysis and Gaussian filtering analysis, have been developed to automatically extract roadway information from satellite images, including the number and location of travel lanes. The results show that the wavelet transformation analysis provides good results for different types of pavements. This study lays the foundation for future development of methods to identify large debris in travel lanes from satellite images after a natural disaster, Such as hurricanes.
The proceedings contain 225 papers. The topics discussed include: super resolution image reconstruction from low resolution aliased images;on the design of a superior irregular LDPC code;adaptive cooperative diversity...
ISBN:
(纸本)9781424419999
The proceedings contain 225 papers. The topics discussed include: super resolution image reconstruction from low resolution aliased images;on the design of a superior irregular LDPC code;adaptive cooperative diversity based on quadrature signaling;3D face representation using scale and transform invariant features;a speaker recognition system using by cross correlation;region-based image segmentation via graph cuts;parametric power spectrum analysis of epileptic seizure;a view of lineaments on East Anatolian Fault Zone using by wavelet analysis method;a graph-based approach for video scene detection;determination of structure boundaries in Archaeological ruins by using Cellular Neural Networks (CNN);analysis of vibration signals related to fuel tank in a passenger coach;and genre and author detection in Turkish texts using artificial immune recognition systems.
In recent years, there has been increased interest in the use of evolutionary algorithms (EAs) in the design of robust image transforms for use in defense and security applications. An EA replaces the defining filter ...
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ISBN:
(纸本)9780819471550
In recent years, there has been increased interest in the use of evolutionary algorithms (EAs) in the design of robust image transforms for use in defense and security applications. An EA replaces the defining filter coefficients of a discrete wavelet transform (DWT) to provide improved image quality within bandwidth-limited imageprocessingapplications, such as the transmission of surveillance data by swarms of unmanned aerial vehicles (UAVs) over shared communication channels. The evolvability of image transform filters depends upon the properties of the underlying fitness landscape traversed by the evolutionary algorithm. The landscape topography determines the ease with which all optimization algorithm may identify highly-fit filters. The properties of a fitness landscape depend upon a chosen evaluation function defined over the space of possible solutions. Evaluation functions appropriate for image filter evolution include mean squared error (MSE), the universal image quality index (UQI), peak signal-to-noise ratio (PSNR), and average absolute pixel error (AAPE). We conduct a theoretical comparison of these image quality measures using random walks through fitness landscapes defined over each evaluation function. This analysis allows us to compare the relative evolvability of the various potential image quality measures by examining fitness topology for each measure in terms of ruggedness and deceptiveness. A theoretical understanding of the topology of fitness landscapes aids in the design of evolutionary algorithms capable of identifying near-optimal image transforms suitable for deployment in defense and security applications of imageprocessing.
wavelet analysis and its applications have become one of the fastest growing research areas in the past several years. wavelet theory has been employed in many fields and applications, such as signal and image process...
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ISBN:
(数字)9789812799524
ISBN:
(纸本)9789812799487
wavelet analysis and its applications have become one of the fastest growing research areas in the past several years. wavelet theory has been employed in many fields and applications, such as signal and imageprocessing, communication systems, biomedical imaging, radar, air acoustics, and endless other areas. Active media technology is concerned with the development of autonomous computational or physical entities capable of perceiving, reasoning, adapting, learning, cooperating, and delegating in a dynamic *** book consists of carefully selected and received papers presented at the conference, and is an attempt to capture the essence of the current state-of-the-art in wavelet analysis and active media technology. Invited papers included in this proceedings includes contributions from Prof P Zhang, T D Bui, and C Y Suen from Concordia University, Canada; Prof N A Strelkov and V L Dol'nikov from Yaroslavl State University, Russia; Prof Chin-Chen Chang and Ching-Yun Chang from Taiwan; Prof S S Pandey from R D University, India; and Prof I L Bloshanskii from Moscow State Regional University, Russia.
A robust image transmission scheme deploying distributed-Alamouti space-time code (STC) over wireless relay networks is proposed. Specifically, we propose a cross-layer design combining application, networking, and ph...
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Recently, the wavelet transform is widely used in multimedia signalprocessingapplications. To provide security solution, the digital watermarking is involved. This study presents a blind wavelet-based watermarking w...
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The paper describes the acquisition and analysis of position-stationary spatial data of spraying processes of hollow cone nozzles through using an imageprocessing based approach. The data source is a CCD camera takin...
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ISBN:
(纸本)9780889867178
The paper describes the acquisition and analysis of position-stationary spatial data of spraying processes of hollow cone nozzles through using an imageprocessing based approach. The data source is a CCD camera taking snapshots of the spraying process. The subsequent analysis aims at automated investigation of characterizing features of the surface waves in varying spraying settings, including arising frequencies/wavelengths and concentration of energy at specific locations respectively frequencies. The bipartite analysis consists of geometric gauging of amplitudes and oscillations as well as of signal decomposition using Fourier-, (Continuous) wavelet-, and S-Transform. This contributes unique information to the prediction of processes associated with spraying. Although the bipartite approach might not be generalizable, it potentially meets a wide range of demands (e.g., in industry, medicine or systems biology) as it provides guidance for reconstructing exposures to sprayed substances for different sites or specific geometric settings. It therefore warrants further investigation.
A new similarity function for region based image fusion is proposed incorporating with Gabor filters and FCM clustering in this paper. First, the fuzzy c-means clustering algorithm (FCM) is used to segment the image i...
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ISBN:
(纸本)9780819467676
A new similarity function for region based image fusion is proposed incorporating with Gabor filters and FCM clustering in this paper. First, the fuzzy c-means clustering algorithm (FCM) is used to segment the image in the feature space formed by multi-channel Gabor filters. Second, wavelet decomposition is performed on the source images, and then the weighting factors are constructed based on the local energy and the new similarity function defined by Gabor filters. Finally, the fused image is obtained by taking inverse wavelet transform. The performance of the image fusion method is evaluated using five criteria including root mean square error, peek-to-peek signal-to-noise ratio, entropy, cross entropy and mutual information. The evaluation results indicate that the proposed image fusion method is effective. Key words fuzzy clustering;Gabor filters;image fusion;multi-scale wavelet decomposition
Multi-channel sensors and multi-channel signal analysis form a specific area of general digital signalprocessing methods with applications in medicine, environmental signal analysis or technology. The paper is devote...
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ISBN:
(纸本)9780889867598
Multi-channel sensors and multi-channel signal analysis form a specific area of general digital signalprocessing methods with applications in medicine, environmental signal analysis or technology. The paper is devoted to general mathematical methods related to initial signal de-noising, detection of its principal components and segmentation to find its specific parts. Feature detection includes the use of discrete wavelet transform (DWT) and discrete Fourier transform (DFT) for estimation of features invariant to signal shift to form clusters of close data segments. The selforganizing neural networks are then used for signal segments classification. Results are numerically evaluated by statistical analysis of distances of individual feature vector values from the corresponding cluster centers. Proposed methods are used for electroencephalogram (EEG) signal segmentation based upon detection of changes of signal spectral components applied to its first principal component, signal segments feature extraction and their classification. Results achieved are compared for different data sets and different mathematical methods used to detect signal segments features. Numerical results are compared with experience of experts specialized to EEG data analysis to allow further correlation with MR images. Proposed methods are accompanied by the appropriate graphical user interface (GUI) designed in the MATLAB environment.
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