This book covers current technological innovations and applications in image processing, introducing analysis techniques and describing applications in remote sensing and manufacturing, among others. The authors include new concepts of color space transformation like color interpolation, among others. Also, the concept of Shearlet Transform and Wavelet Transform and their implementation are discussed. The authors include a perspective about concepts and techniques of remote sensing like image mining, geographical, and agricultural resources. The book also includes several applications of human organ biomedical image analysis. In addition, the principle of moving object detection and tracking — including recent trends in moving vehicles and ship detection – is described. Presents developments of current research in various areas of image processing; Includes applications of image processing in remote sensing, astronomy, and manufacturing; Pertains to researchers, academics, students, and practitioners in image processing.

Digital image processing, originally established to analyze and improve lunar images, is rapidly growing into a wealth of new appli cations, due to the enormous technical progress made in computer engineering. At present, the most important fields of growth appear to emerge in the areas of medical image processing (i. e. tomography, thermography), earth resource inventory (i. e. land usage, minerals), office automation (i. e. document storage, retrieval and reproduction) and industrial production (i. e. computer vision for mechanical ro bots). Currently, emphasis is being shifted from signal-processing re search and design-innovation activities towards cost-efficient system implementations for interactive digital image processing. For the years ahead, trends in computer engineering indicate still further advances in Large Scale Integration (LSI) and Input/Output (I/O) technologies allowing the implementation of powerful parallel and/or distributed processor architectures for real-time processing of high resolution achromatic and color images. In view of the many new developments in the field of digital image processing and recognizing the importance of discussing these developments amongst key scientists that might make use of them, ffiM Germany sponsored an international symposium on 'Advances in Digital Image Processing', held at Bad Neuenahr, Federal Republic of Germany, September 26 - 28, 1978. The interest shown in this symposium encouraged the publi cation of the papers presented in this volume of the ffiM Research Symposium Series.

This book covers the technology of digital image processing in various fields with big data and their applications. Readers will understand various technologies and strategies used in digital image processing as well as handling big data, using machine-learning techniques. This book will help to improve the skills of students and researchers in such fields as engineering, agriculture, and medical imaging. There is a need to be able to understand and analyse the latest developments of digital image technology. As such, this book will cover: · Applications such as biomedical science and biometric image processing, content-based image retrieval, remote sensing, pattern recognition, shape and texture analysis · New concepts in color interpolation to produce the full color from the sub-pattern bare pattern color prevalent in today's digital cameras and other imaging devices · Image compression standards that are needed to serve diverse applications · Applications of remote sensing, medical science, traffic management, education, innovation, and analysis in agricultural design and image processing · Both soft and hard computing approaches at great length in relation to major image processing tasks · The direction and development of current and future research in many areas of image processing · A comprehensive bibliography for additional research (integrated within the framework of the book) This book focuses not only on theoretical and practical knowledge in the field but also on the traditional and latest tools and techniques adopted in image processing and data science. It also provides an indispensable guide to a wide range of basic and advanced techniques in the fields of image processing and data science.

Similar to the way in which computer vision and computer graphics act as the dual fields that connect image processing in modern computer science, the field of image processing can be considered a crucial middle road between the vision and graphics fields. Research Developments in Computer Vision and Image Processing: Methodologies and Applications brings together various research methodologies and trends in emerging areas of application of computer vision and image processing. This book is useful for students, researchers, scientists, and engineers interested in the research developments of this rapidly growing field.

Deep learning enables a model constituted by multiple processing layers to learn the data representation with multiple levels of abstraction. In the past decade, deep learning has brought remarkable achievements in many fields of machine learning and pattern recognition, especially in image processing. The state-of-the-art performance in image super-resolution reconstruction, image classification, target detection, image retrieval and other image processing tasks have been greatly improved. This book introduces these image processing technologies based on deep learning, including recent advances, applications in real scenes and future trends. The first chapter introduces image super-resolution reconstruction, which aims to recover high-resolution images from corresponding low-resolution versions. This chapter reviews these image super-resolution methods based on convolutional neural networks and generative adversarial networks on account of internal network structure. The second chapter presents four categories of few-shot image classification algorithms: transfer learning based, meta-learning based, data augmentation based, and multimodal based methods. In the third chapter, deep learning based models for small target detection in video are summarized in detail, which are categorized into one-stage models and two-stage models according to the detection stages. The network structures and plug-in modules for video based small target detection are also explained. The fourth chapter discusses deep learning based cross-modal hashing for image retrieval methods, including the extraction of high-level semantic information and the maintenance of similarity between different mo

Image processing-from basics to advanced applications Learn how to master image processing and compression with this outstanding state-of-the-art reference. From fundamentals to sophisticated applications, Image Processing: Principles and Applications covers multiple topics and provides a fresh perspective on future directions and innovations in the field, including: * Image transformation techniques, including wavelet transformation and developments * Image enhancement and restoration, including noise modeling and filtering * Segmentation schemes, and classification and recognition of objects * Texture and shape analysis techniques * Fuzzy set theoretical approaches in image processing, neural networks, etc. * Content-based image retrieval and image mining * Biomedical image analysis and interpretation, including biometric algorithms such as face recognition and signature verification * Remotely sensed images and their applications * Principles and applications of dynamic scene analysis and moving object detection and tracking * Fundamentals of image compression, including the JPEG standard and the new JPEG2000 standard Additional features include problems and solutions with each chapter to help you apply the theory and techniques, as well as bibliographies for researching specialized topics. With its extensive use of examples and illustrative figures, this is a superior title for students and practitioners in computer science, wireless and multimedia communications, and engineering.

Interest in computer vision and image processing has grown in recent years with the advancement of everyday technologies such as smartphones, computer games, and social robotics. These advancements have allowed for advanced algorithms that have improved the processing capabilities of these technologies. Advancements in Computer Vision and Image Processing is a critical scholarly resource that explores the impact of new technologies on computer vision and image processing methods in everyday life. Featuring coverage on a wide range of topics including 3D visual localization, cellular automata-based structures, and eye and face recognition, this book is geared toward academicians, technology professionals, engineers, students, and researchers seeking current research on the development of sophisticated algorithms to process images and videos in real time.