IMAGE QUALITY ENHANCEMENT USING FUSION TECHNIQUE PDF Download

Author: KAPIL JOSHI
Publisher: Book Rivers
ISBN: 9355151756
Category : Antiques & Collectibles
Languages : en
Pages : 178

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Book Description

Author: Luciano Alparone
Publisher: CRC Press
ISBN: 1466587504
Category : Science
Languages : en
Pages : 328

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Book Description
A synthesis of more than ten years of experience, Remote Sensing Image Fusion covers methods specifically designed for remote sensing imagery. The authors supply a comprehensive classification system and rigorous mathematical description of advanced and state-of-the-art methods for pansharpening of multispectral images, fusion of hyperspectral and

Author: Yufeng Zheng (Associate professor)
Publisher:
ISBN: 9781510619067
Category : Computer vision
Languages : en
Pages : 396

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Book Description
"This book provides a complete overview of the state of the art in color image fusion, the associated evaluation methods, and its range of applications. It presents a comprehensive overview of fusion metrics and a comparison of objective metrics and subjective evaluations. Part I addresses the historical background and basic concepts. Part II describes image fusion theory. Part III focuses on quantitative and qualitative evaluation. Part IV presents several fusion applications, including two primary multiscale fusion approaches - the image pyramid and wavelet transform - as they pertain to face matching, biomedical imaging, and night vision"--

Author: Tania Stathaki
Publisher: Elsevier
ISBN: 0080558526
Category : Technology & Engineering
Languages : en
Pages : 519

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Book Description
The growth in the use of sensor technology has led to the demand for image fusion: signal processing techniques that can combine information received from different sensors into a single composite image in an efficient and reliable manner. This book brings together classical and modern algorithms and design architectures, demonstrating through applications how these can be implemented. Image Fusion: Algorithms and Applications provides a representative collection of the recent advances in research and development in the field of image fusion, demonstrating both spatial domain and transform domain fusion methods including Bayesian methods, statistical approaches, ICA and wavelet domain techniques. It also includes valuable material on image mosaics, remote sensing applications and performance evaluation. This book will be an invaluable resource to R&D engineers, academic researchers and system developers requiring the most up-to-date and complete information on image fusion algorithms, design architectures and applications. - Combines theory and practice to create a unique point of reference - Contains contributions from leading experts in this rapidly-developing field - Demonstrates potential uses in military, medical and civilian areas

Author: Gang Xiao
Publisher: Springer Nature
ISBN: 9811548676
Category : Computers
Languages : en
Pages : 415

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Book Description
This book systematically discusses the basic concepts, theories, research and latest trends in image fusion. It focuses on three image fusion categories – pixel, feature and decision – presenting various applications, such as medical imaging, remote sensing, night vision, robotics and autonomous vehicles. Further, it introduces readers to a new category: edge-preserving-based image fusion, and provides an overview of image fusion based on machine learning and deep learning. As such, it is a valuable resource for graduate students and scientists in the field of digital image processing and information fusion.

Author: Gustau Camps-Valls
Publisher: John Wiley & Sons
ISBN: 1119646162
Category : Technology & Engineering
Languages : en
Pages : 436

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Book Description
DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and treatment of the concepts, skills, and practices necessary to quickly become familiar with the application of deep learning techniques to the Earth sciences. The book prepares readers to be ready to use the technologies and principles described in their own research. The distinguished editors have also included resources that explain and provide new ideas and recommendations for new research especially useful to those involved in advanced research education or those seeking PhD thesis orientations. Readers will also benefit from the inclusion of: An introduction to deep learning for classification purposes, including advances in image segmentation and encoding priors, anomaly detection and target detection, and domain adaptation An exploration of learning representations and unsupervised deep learning, including deep learning image fusion, image retrieval, and matching and co-registration Practical discussions of regression, fitting, parameter retrieval, forecasting and interpolation An examination of physics-aware deep learning models, including emulation of complex codes and model parametrizations Perfect for PhD students and researchers in the fields of geosciences, image processing, remote sensing, electrical engineering and computer science, and machine learning, Deep Learning for the Earth Sciences will also earn a place in the libraries of machine learning and pattern recognition researchers, engineers, and scientists.

Author: Gabriel Cristóbal
Publisher: Springer Nature
ISBN: 3030392120
Category : Science
Languages : en
Pages : 303

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Book Description
High-resolution images of phytoplankton cells such as diatoms or desmids, which are useful for monitoring water quality, can now be provided by digital microscopes, facilitating the automated analysis and identification of specimens. Conventional approaches are based on optical microscopy; however, manual image analysis is impractical due to the huge diversity of this group of microalgae and its great morphological plasticity. As such, there is a need for automated recognition techniques for diagnostic tools (e.g. environmental monitoring networks, early warning systems) to improve the management of water resources and decision-making processes. Describing the entire workflow of a bioindicator system, from capture, analysis and identification to the determination of quality indices, this book provides insights into the current state-of-the-art in automatic identification systems in microscopy.

Author: Jan Egger
Publisher: Academic Press
ISBN: 0128234237
Category : Computers
Languages : en
Pages : 284

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Book Description
Computer-Aided Oral and Maxillofacial Surgery: Developments, Applications, and Future Perspectives is an ideal resource for biomedical engineers and computer scientists, clinicians and clinical researchers looking for an understanding on the latest technologies applied to oral and maxillofacial surgery. In facial surgery, computer-aided decisions supplement all kind of treatment stages, from a diagnosis to follow-up examinations. This book gives an in-depth overview of state-of-the-art technologies, such as deep learning, augmented reality, virtual reality and intraoperative navigation, as applied to oral and maxillofacial surgery. It covers applications of facial surgery that are at the interface between medicine and computer science. Examples include the automatic segmentation and registration of anatomical and pathological structures, like tumors in the facial area, intraoperative navigation in facial surgery and its recent developments and challenges for treatments like zygomatic implant placement. - Provides comprehensive, state-of-the-art knowledge of interdisciplinary applications in facial surgery - Presents recent algorithmic developments like Deep Learning, along with recent devices in augmented reality and virtual reality - Includes clinical knowledge of two facials surgeons who give insights into the current clinical practice and challenges of facial surgeons in university hospitals in Austria and China

Author: Shubham Mahajan
Publisher: John Wiley & Sons
ISBN: 1394230931
Category : Computers
Languages : en
Pages : 372

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Book Description
A comprehensive book providing high-quality research addressing challenges in theoretical and application aspects of soft computing and machine learning in image processing and computer vision. Researchers are working to create new algorithms that combine the methods provided by CI approaches to solve the problems of image processing and computer vision such as image size, noise, illumination, and security. The 19 chapters in this book examine computational intelligence (CI) approaches as alternative solutions for automatic computer vision and image processing systems in a wide range of applications, using machine learning and soft computing. Applications highlighted in the book include: diagnostic and therapeutic techniques for ischemic stroke, object detection, tracking face detection and recognition; computational-based strategies for drug repositioning and improving performance with feature selection, extraction, and learning; methods capable of retrieving photometric and geometric transformed images; concepts of trading the cryptocurrency market based on smart price action strategies; comparative evaluation and prediction of exoplanets using machine learning methods; the risk of using failure rate with the help of MTTF and MTBF to calculate reliability; a detailed description of various techniques using edge detection algorithms; machine learning in smart houses; the strengths and limitations of swarm intelligence and computation; how to use bidirectional LSTM for heart arrhythmia detection; a comprehensive study of content-based image-retrieval techniques for feature extraction; machine learning approaches to understanding angiogenesis; handwritten image enhancement based on neutroscopic-fuzzy. Audience The book has been designed for researchers, engineers, graduate, and post-graduate students wanting to learn more about the theoretical and application aspects of soft computing and machine learning in image processing and computer vision.

Author: Deepika Koundal
Publisher: Academic Press
ISBN: 0128204117
Category : Computers
Languages : en
Pages : 324

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Book Description
Advances in Computational Techniques for Biomedical Image Analysis: Methods and Applications focuses on post-acquisition challenges such as image enhancement, detection of edges and objects, analysis of shape, quantification of texture and sharpness, and pattern analysis. It discusses the archiving and transfer of images, presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing. It examines various feature detection and segmentation techniques, together with methods for computing a registration or normalization transformation. Advances in Computational Techniques for Biomedical Image Analysis: Method and Applications is ideal for researchers and post graduate students developing systems and tools for health-care systems. - Covers various challenges and common research issues related to biomedical image analysis - Describes advanced computational approaches for biomedical image analysis - Shows how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. - Explores a range of computational algorithms and techniques, such as neural networks, fuzzy sets, and evolutionary optimization - Explores cloud based medical imaging together with medical imaging security and forensics