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Proceedings of the 1999 mathematics of data/image coding, compression, and encryption II

作者： Caimi, Frank M. Hassan, Gamal A. Florida Inst of Technology Melbourne United States

In underwater acoustic communication, (ACOMMs), ocean surface and bottom conditions create multi path propagation's for the transmitted signal that result in Inter symbol Interference (ISI) at the receiver. Generally, Equalization, Diversity / Beam forming, and Channel coding are three independent techniques that are used to improve received signal quality. Equalization compensates for ISI created by a band-limited, time-dispersive channel through implementation of specialized filtering schemes within the receiver. The coefficients of the equalizer need to be continuously adjusted to compensate for the variability in the channel. Since the number of states required by the equalizer (or beam former) is finite, and may be described over a limited set of operating conditions (environments), it is worthwhile to consider a pattern recognition approach for identifying channel conditions and subsequent equalizer state specifications. This paper describes the approach and preliminary results obtained form the use of pattern recognition techniques to select a set of `best choice' equalizer coefficients and to decode a signal sequence directly. The method does not rely on the application of any adaptive algorithm for estimation of the equalizer coefficients during the actual data transmission or reception. Expectations are that performance benefits may be gained in those cases where adaptive algorithms fail to select the optimal filter coefficients due to computational complexity or other factors.

关键词： image communication systems

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Applied mathematics 1

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丛书名： mathematics Textbooks for Science and Engineering

1000年

作者： Charles K. Chui Qingtang Jiang

ISBN: (数字)9789462390096

ISBN: (纸本)9789462390089

This textbook, apart from introducing the basic aspects of applied mathematics, focuses on recent topics such as information data manipulation, information coding, data approximation, data dimensionality reduction, data compression, time-frequency and time scale bases, image manipulation, and image noise removal. The methods treated in more detail include spectral representation and “frequency” of the data, providing valuable information for, e.g. data compression and noise removal. Furthermore, a special emphasis is also put on the concept of “wavelets” in connection with the “multi-scale” structure of data-sets. The presentation of the book is elementary and easily accessible, requiring only some knowledge of elementary linear algebra and calculus. All important concepts are illustrated with examples, and each section contains between 10 an 25 exercises. A teaching guide, depending on the level and discipline of instructions is included for classroom teaching and self-study.

关键词： applications of mathematics Information and Communication, Circuits Statistics, general Computer Imaging, Vision, pattern Recognition and Graphics Engineering Design

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Erratum: (mathematics of data/image coding, compression, and encryption IV, with applications (30-31 July 2001))

Proceedings of SPIE - The International Society for Optical ...

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Proceedings of SPIE - The International Society for Optical Engineering 2001年 4475卷 285-285页

作者： Schmalz, Mark S.

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Wavelet Transforms and Their applications 1

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1000年

作者： Lokenath Debnath

ISBN: (数字)9781461200970

Overview Historically, the concept of "ondelettes" or "wavelets" originated from the study of time-frequency signal analysis, wave propagation, and sampling theory. One of the main reasons for the discovery of wavelets and wavelet transforms is that the Fourier transform analysis does not contain the local information of signals. So the Fourier transform cannot be used for analyzing signals in a joint time and frequency domain. In 1982, Jean MorIet, in collaboration with a group of French engineers, first introduced the idea of wavelets as a family of functions constructed by using translation and dilation of a single function, called the mother wavelet, for the analysis of nonstationary signals. However, this new concept can be viewed as the synthesis of various ideas originating from different disciplines including mathematics (Calder6n-Zygmund operators and Littlewood-Paley theory), physics (coherent states in quantum mechanics and the renormalization group), and engineering (quadratic mirror filters, sideband coding in signal processing, and pyramidal algorithms in image processing). Wavelet analysis is an exciting new method for solving difficult problems in mathematics, physics, and engineering, with modern applications as diverse as wave propagation, data compression, image processing, pattern recognition, computer graphics, the detection of aircraft and submarines, and improvement in CAT scans and other medical image technology. Wavelets allow complex information such as music, speech, images, and patterns to be decomposed into elementary forms, called the fundamental building blocks, at different positions and scales and subsequently reconstructed with high precision.

关键词： Electrical Engineering Signal, image and Speech Processing Functional Analysis applications of mathematics

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image Representation and Processing 1

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丛书名： mathematics and Its applications

1000年

作者： V. V. Alexandrov N. D. Gorsky

ISBN: (数字)9789401117470

ISBN: (纸本)9780792321361;9789401047661

Recently, much attention has been paid to image processing with multiresolution and hierarchical structures such as pyramids and trees. This volume deals with recursive pyramids, which combine the advantages of available multiresolution structures and which are convenient both for global and local image processing. Recursive pyramids are based on regular hierarchical (recursive) structures containing data on image fragments of different sizes. Such an image representation technique enables the effective manipulation of pictorial information as well as the development of special hardware or data structures. The major aspects of this book are two original mathematical models of greyscale and binary images represented by recursive structures. image compression, transmission and processing are discussed using these models. A number of applications are presented, including optical character recognition, expert systems and special computer architecture for pictorial data processing. The majority of results are presented as algorithms applicable to discrete information fields of arbitrary dimensions (e.g. 2-D or 3-D images).;The book is divided into six chapters: Chapter 1 provides a brief introduction. Chapter 2 then deals with recursive structures and their properties. Chapter 3 introduces pyramidal image models. image coding and the progressive transmission of images with gradual refinement are discussed in Chapter 4. Chapters 5 and 6 are devoted to image processing with pyramidal-recursive structures and applications. The volume concludes with a comprehensive bibliography.;For applied mathematicians and computer scientists whose work involves computer vision, information theory and other aspects of image representation techniques.

关键词： coding and Information Theory Computer Imaging, Vision, pattern Recognition and Graphics Computer Systems Organization and Communication Networks

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A Novel Algorithm for image compression and pattern Matching

A Novel Algorithm for Image Compression and Pattern Matching

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International Conference on Advances in Computing and Communications (ICACC)

作者： Shamna P Tripti C Paul Augustine Department of Computer Science Rajagiri School of Engineering & Technology Kochi 39 Kerala India

The development in communication and use of multimedia applications has created a remarkable demand for robust ways to store and transmit large databases of images. The current communication system demands compression techniques to store and transmit data in an apposite manner. compression schemes for images can be used to manage data of high sensitivity with less computational complexity. In this paper we suggest a novel algorithm for image compression and pattern matching called Difference Component Analysis (DCA). DCA extract the most relevant image feature components that identify the image. The DCA is based on the premise that matching images have minimal difference components. The experiment on DCA is done using more than 1000 human face images. The results show that the image can be compressed to a single decimal value and uses less computational steps. The concept can be applied for pattern recognition encryption techniques.

关键词： image coding databases pattern matching Face encryption Training Bandwidth

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Reversible data hiding technique for stream ciphered and wavelet compressed image

Reversible data hiding technique for stream ciphered and wav...

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International Conference on pattern Recognition, Informatics and Medical Engineering

作者： S. Imaculate Rosaline C. Rengarajaswamy Department of Electronics and Communication Engineering Oxford Engineering College Department of Electronics and Communication Engineering Oxford Engineering College India

Reversible data Hiding (RDH) Technique aims in recovering back the original content from the marked media. The original image is desirable in some applications. Thus, RDH plays a vital role in such situations. Securing the multimedia content can be achieved by performing encryption. Transmission time is further decreased by compressing such encrypted images. The process of compression reduces the amount of data required for representing the image. The content owner thus encrypts the original image using Stream Cipher process. The encrypted image is then used as the media for hiding secret image. The embedded image can then be compressed using wavelet compression. The receiver does all the three processes in reverse for getting back the original image and the secret image. Thus the compressed image is first decompressed. Second, the data hiding key is employed to extract the secret message. Third, the encryption key is employed to decrypt and get back the original content. Thus this paper focuses on achieving better security and improved transmission rate.

关键词： image coding Ciphers Streaming media encryption Wavelet transforms

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Fractal video compression for IOT-based smart cities applications using motion vector estimation

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Measurement: Sensors 2023年 26卷

作者： Jang Bahadur Saini, Dilip Kumar Kamble, Shailesh D. Shankar, Ravi Kumar, M. Ranjith Kapila, Dhiraj Tripathi, Durga Prasad de, Arunava Department of Computer Science and Engineering Himalayan School of Science & Technology Swami Rama Himalayan University Uttarakhand India Department of Artificial Intelligence and Data Science Indira Gandhi Delhi Technical University for Women Delhi India Department of Electronics and Communication Engineering SR University Warangal India Department of Mathematics Amrita School of Engineering Amrita Vishwa Vidyapeetham Tamil Nadu Chennai India Department of Computer Science & Engineering Lovely Professional University Punjab Phagwara India Department of Electronics & Communication Koneru Lakshmaiah Education Foundation Andhra pradesh Vaddesearam522302 India Department of Electronics & Communication Asansol Engineering College West bangal Kanyapur India

Recently, Internet of the things (IoTs) devices have been used highly in surveillance applications in smart environments, cities, and buildings. Most of the surveillance data recorded by the IoT devices is in the form of video and needs to be transmitted to the admin or server by video streaming technology. Fractal video compression uses a self-similarity concept for video compression, meaning the fractal image contains self-similarity of itself that is explained and denoted by change. Computational cost is more in fractal video coding;different methods have been developed to reduce this computational cost. The proposed work's main objective is to implement a video streaming approach by combining the Diamond-search-pattern- block-matching motion estimation algorithm and hash-based fractal video compression algorithm to reduce the encoding time. It improves both the delay and security of the block matching system and the developed approach measures based on evaluation parameters: Peak signal-to-noise ratio (PSNR), encoding time, decoding time, Mean squared error (MSE), and compression ratio for Smart City applications. Compared to other algorithms, the IoTs video data is streamed efficiently in a smart city to analyse the abnormalities. © 2023 The Authors

关键词： Internet of things

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EDITORIAL SPECIAL ISSUE: PART IV-III-II-I SERIES - FRACTALS-FRACTIONAL AI-BASED ANALYSES AND applications TO COMPLEX SYSTEMS finestre of creativity, complexity and universality…

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FRACTALS-COMPLEX GEOMETRY patternS AND SCALING IN NATURE AND SOCIETY 2023年第10期31卷 2302005-2302005页

作者： Karaca, Yeliz Baleanu, Dumitru Moonis, Majaz Zhang, Yu-dong Gervasi, Osvaldo Univ Massachusetts Chan Med Sch 55 Lake Ave North Worcester MA 01655 USA Lebanese Amer Univ Beirut 11022 Lebanon Inst Space Sci Bucharest 077125 Romania Univ Leicester Univ Rd Leicester LE1 7RH England Univ Perugia I-06123 Perugia Italy

Complex systems, as interwoven miscellaneous interacting entities that emerge and evolve through self-organization in a myriad of spiraling contexts, exhibit subtleties on global scale besides steering the way to understand complexity which has been under evolutionary processes with unfolding cumulative nature wherein order is viewed as the unifying framework. Indicating the striking feature of non-separability in components, a complex system cannot be understood in terms of the individual isolated constituents' properties per se, it can rather be comprehended as a way to multilevel approach systems behavior with systems whose emergent behavior and pattern transcend the characteristics of ubiquitous units composing the system itself. This observation specifies a change of scientific paradigm, presenting that a reductionist perspective does not by any means imply a constructionist view;and in that vein, complex systems science, associated with multiscale problems, is regarded as ascendancy of emergence over reductionism and level of mechanistic insight evolving into complex system. While evolvability being related to the species and humans owing their existence to their ancestors' capability with regards to adapting, emerging and evolving besides the relation between complexity of models, designs, visualization and optimality, a horizon that can take into account the subtleties making their own means of solutions applicable is to be entailed by complexity. Such views attach their germane importance to the future science of complexity which may probably be best regarded as a minimal history congruent with observable variations, namely the most parallelizable or symmetric process which can turn random inputs into regular outputs. Interestingly enough, chaos and nonlinear systems come into this picture as cousins of complexity which with tons of its components are involved in a hectic interaction with one another in a nonlinear fashion amongst the other related systems

关键词： Applied mathematics Computational mathematics Pure mathematics Mathematical Sciences Discrete mathematics Mathematical Physics Theoretical Sciences Exact Science Computational Methods Computational Intelligence Applied Sciences Computer Science Computational Science data Science Engineering Electrical and Electronics Engineering Exact Sciences Natural Sciences Social Sciences Nonlinear Dynamics Nonlinear Systems Linear Systems Fractional Calculus AI Control Control Systems Optimization Complexity Chaos Uncertainty Causality Symmetry Oscillations Bifurcation Stability Sensitivity Quantum Medicine Biology Physics Chemistry Mathematical Bioengineering Mathematical Neuroscience Mathematical Biology Artificial Intelligence Neural Networks Artificial Neural Networks data-Driven Models encryption Soft Computing coding Theory Machine Learning Deep Learning Intelligent Systems Probabilities and Stochastic Processes Game Theory Solitons, Fractals, Multifractals Fractional Calculus Fractional Dynamics Fractional mathematics Fractional Systems Fractional Models Fractals Multifractals Waves Wavelet Entropy Algebraic Methods Computational (-Algorithmic) Complexity Fractional Order Differential Equations Fractional Differential Equations Fuzzy Fractional Differential Equations Special Functions Functional Analysis Error Estimations Fuzzy Calculus Differential/Integral Equations, Stochastic Differential Equations, Fractal-Fractional Differential Equations Fractional-Order Controllers Fractional-Order Systems Intelligent Fractional Order Systems Variational Principles image and/or Signal Processing Mathematical Models Fractal AI Fractional AI Fractals-Fractional AI Quantum AI Dynamical systems Chaotic Systems Complex Systems

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