Octonion Sparse-Based Image Processing
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Über dieses Buch
This book uncovers the innovative features of complex algebra i.e., the octonion -sparse concept in image processing and how it can help in improving the computational efficiency of image processing.
It deals with the most common octonion convolution neural network, quaternion wavelet, and sparse representation-based techniques in multispectral image processing.
The book focusses on how evolution in algebraic concepts i.e. octonion and sparse helps in improving accuracy and efficiency of various color image restoration, reconstruction and recognition.
It provides examples of research and real-world applications related to biometric security, medical image processing, face recognition, and how crucial characteristics are extracted.
The main focus of this book is to bring all the related technologies, novel findings and managerial applications of Colored Medical Imaging on a single platform to provide great readability, easy understanding, and smooth adaptability of various basic and advanced concepts to the Undergraduate and Postgraduate students, Researchers, Managers, Designers, Academicians, and Practitioners doing work in this domain.
Information zu Autoren / Herausgebern
Dr. Satya Prakash Yadav is currently the Associate Professor of the School of Computer Science Engineering and Technology, Bennett University, Greater Noida (India) and has completed Postdoctoral Research Fellow from Federal Institute of Education, Science and Technology of Ceará, Brazil. He has awarded his PhD degree from Dr. A.P.J. Abdul Kalam Technical University (AKTU) (formerly UPTU). A prolific writer, Dr. Satya Prakash Yadav has published two patents and authored many research papers in web of science indexed journals. Additionally, he has presented research papers at many conferences in the areas of Image Processing, Information retrieval, Features extraction and Programming, such Digital Image Processing, Feature Extraction, Information Retrieval, C, Data Structure, C++, C# and Java. Also, he is a Editor in Chief in Journal of Cyber Security in Computer System (MAT journals), Series Editor in Bentham Science and Lead Editor in CRC Press, Taylor and Francis Group Publisher (U.S.A), Tech Science Press (Computer Systems Science and Engineering), Human-Centric Intelligent Systems -International Springer Publisher, Science Publishing Group, (U.S.A), and Eureka Journals, Pune ( India).
Prof. (Dr.) Abhay Bansal (SMIEEE) is the Professor and Dean of School of Computer Science Engineering & Technology and Dean, International Affairs and Corporate Outreach (IRCO). Dr. Abhay Bansal has over 29 years of Industry and Academic Experience. He has more than 130+ papers in various international journals/conferences of repute. He has guided more than 10 PhD fellows. Dr. Bansal is also Microsoft Certified Professional, and Microsoft approved Technical Associate. Dr. Bansal is also AWS Certified Cloud Practitioner & Solution Architect. He is also Authorized Trainer of AWS Cloud and has trained 2000+ students in last 2 years. He is a great administrator and an astute leader.
Prof. Dr. Victor Hugo C. de Albuquerque (Senior Member of IEEE) is currently a Professor and Senior Researcher at the Department of Teleinformatics Engineering (DETI)/Graduate Program in Teleinformatics Engineering (PPGETI) at the Federal University of Ceará (UFC), Brazil. He earned a Ph.D in Mechanical Engineering from the Federal University of Paraíba (UFPB, 2010), a MSc in Teleinformatics Engineering from the PPGETI/UFC (UFC, 2007). He completed a BSE in Mechatronics Engineering at the Federal Center of Technological Education of Ceará (CEFETCE, 2006).
Prof. Dr. Fadi Al-Turjman received his Ph.D. in computer science from Queen’s University, Canada, in 2011. He is the associate dean for research and the founding director of the International Research Center for AI and IoT at Near East University, Nicosia, Cyprus. Prof. Al-Turjman is the head of Artificial Intelligence Engineering Dept., and a leading authority in the areas of smart/intelligent IoT systems, wireless, and mobile networks’ architectures, protocols, deployments, and performance evaluation in Artificial Intelligence of Things (AIoT).
Prof. (Dr.) Houbing Herbert Song, Ph.D., is an Associate Professor whose research interests include cyber-physical systems/internet of things, cybersecurity and privacy, and AI/machine learning/big data analytics. His research has been sponsored by federal agencies (including National Science Foundation, US Department of Transportation, and Federal Aviation Administration, among others.) He is the Director of the NSF Center for Aviation Big Data Analytics (Planning), the Associate Director for Leadership of the DOT Transportation Cybersecurity Center for Advanced Research and Education (Tier 1 Center) and the Director of the Security and Optimization for Networked Globe Laboratory, SONG Lab, at UMBC.
Fachgebiete
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Frontmatter
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Preface
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Contents
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List of authors
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1 Introduction to octonion sparse medical image process
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2 Octonion sparse mathematics: theory and practice
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3 Octonion sparse representation of multispectral innovative stereoimage classification
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4 Octonion-sparse-based image processing: applications, benefits, and future challenges
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5 Technical challenges in using octonion complex algebra for multimodal and multispectral image processing
51 -
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6 Octonion differential equations for multimodal and multispectral color image processing
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7 Octonion cooler sparse representations for image processing: a technical review
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8 Octonion sparse matrix optimization
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9 Collaborative and sparse representation of color image processing
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10 Robust sparse representation in octonion space for multimodal image processing
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11 Sparse representation-based regularization for multimodal and multispectral image processing
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12 Fusion of multimodal, multispectral image processing using octonion principal component analysis
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13 Experimental evaluation and validation of different variants of PCA on octonion multispectral imaging
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14 Octonion wavelet transformation for image processing: application, benefits, and future challenges
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15 Discrete wavelet transformation on octonion space
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16 De-noising in color images using octonion discrete wavelet transformation
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17 Fundamentals of hypercomplex Fourier transform in octonion space
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18 Application of hypercomplex Fourier transform in octonion space for skin image classification
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19 Octonion neural network: types of applications, benefits, and future challenges for multispectral image processing
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20 Octonion neural network for geometrical operators in high-dimensional quaternion space
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21 Image dehazing using octonion complex algebra-based neural networks
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22 Classification of multispectral imaging using octonion convolution neural network
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23 Optimizing top precision performance measure of content-based image retrieval by learning similarity function
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24 Phasor octonion neural network for multimodal image processing
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Index
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Mathematical Methods in the Digital Age
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