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  • 1
    Book
    Book
    Cambridge, United Kingdom :Cambridge University Press,
    UID:
    almahu_BV046429185
    Format: xxi, 574 Seiten : , Illustrationen, Diagramme.
    Edition: Second edition
    ISBN: 978-1-108-48072-7
    Language: English
    Subjects: Computer Science , Psychology
    RVK:
    RVK:
    RVK:
    Keywords: Künstliche Intelligenz ; Maschinelles Lernen ; Kognitionswissenschaft ; Mensch-Maschine-Kommunikation
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  • 2
    Book
    Book
    Berlin ; Heidelberg : Springer-Verlag GmbH
    UID:
    b3kat_BV005485677
    Format: XIV, 243 Seiten , Illustrationen, Diagramme
    ISBN: 3540532927 , 0387532927 , 9783642635052 , 9783642582165
    Series Statement: Springer series in information sciences 23
    Note: Hier auch später erschienene, unveränderte Nachdrucke , Literaturangaben
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Bildrekonstruktion ; Bildverarbeitung ; Bildverarbeitung ; Bilderkennung ; Signalverarbeitung ; Information Retrieval ; Wiederherstellung ; Aufsatzsammlung
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  • 3
    Book
    Book
    Berlin ; Heidelberg :Springer-Verlag GmbH,
    UID:
    almafu_BV005485677
    Format: XIV, 243 Seiten : , Illustrationen, Diagramme.
    ISBN: 3-540-53292-7 , 0-387-53292-7 , 978-3-642-63505-2 , 978-3-642-58216-5
    Series Statement: Springer series in information sciences 23
    Note: Hier auch später erschienene, unveränderte Nachdrucke. - Literaturangaben
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Bildrekonstruktion ; Bildverarbeitung ; Bildverarbeitung ; Bilderkennung ; Signalverarbeitung ; Information Retrieval ; Wiederherstellung ; Aufsatzsammlung
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  • 4
    UID:
    almahu_9948621069202882
    Format: XX, 288 p. , online resource.
    Edition: 1st ed. 1997.
    ISBN: 9781475725667
    Content: One of the most intriguing problems in video processing is the removal of the redundancy or the compression of a video signal. There are a large number of applications which depend on video compression. Data compression represents the enabling technology behind the multimedia and digital television revolution. In motion compensated lossy video compression the original video sequence is first split into three new sources of information, segmentation, motion and residual error. These three information sources are then quantized, leading to a reduced rate for their representation but also to a distorted reconstructed video sequence. After the decomposition of the original source into segmentation, mo­ tion and residual error information is decided, the key remaining problem is the allocation of the available bits into these three sources of information. In this monograph a theory is developed which provides a solution to this fundamental bit allocation problem. It can be applied to all quad-tree-based motion com­ pensated video coders which use a first order differential pulse code modulation (DPCM) scheme for the encoding of the displacement vector field (DVF) and a block-based transform scheme for the encoding of the displaced frame differ­ ence (DFD). An optimal motion estimator which results in the smallest DFD energy for a given bit rate for the encoding of the DVF is also a result of this theory. Such a motion estimator is used to formulate a motion compensated interpolation scheme which incorporates a global smoothness constraint for the DVF.
    Note: 1 Introduction -- 2 Review of Lossy Video Compression -- 3 Background -- 4 General Contributions -- 5 Optimal Motion Estimation and Motion Compensated Interpolation for Video Compression -- 6 A Video Compression Scheme with Optimal Bit Allocation Between Displacement Vector Field and Displaced Frame Difference -- 7 A Video Compression Scheme with Optimal Bit Allocation Among Segmentation, Motion and Residual Error -- 8 An Optimal Polygonal Boundary Encoding Scheme -- References.
    In: Springer Nature eBook
    Additional Edition: Printed edition: ISBN 9781441951724
    Additional Edition: Printed edition: ISBN 9780792398509
    Additional Edition: Printed edition: ISBN 9781475725674
    Language: English
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  • 5
    UID:
    almahu_9948621266702882
    Format: XVI, 302 p. , online resource.
    Edition: 1st ed. 1998.
    ISBN: 9781475765144
    Content: Signal Recovery Techniques for Image and Video Compression and Transmission establishes a bridge between the fields of signal recovery and image and video compression. Traditionally these fields have developed separately because the problems they examined were regarded as very different, and the techniques used appear unrelated. Recently, though, there is growing consent among the research community that the two fields are quite closely related. Indeed, in both fields the objective is to reconstruct the best possible signal from limited information. The field of signal recovery, which is relatively mature, has long been associated with a wealth of powerful mathematical techniques such as Bayesian estimation and the theory of projects onto convex sets (to name just two). This book illustrates for the first time in a complete volume how these techniques can be brought to bear on the very important problems of image and video compression and transmission. Signal Recovery Techniques for Image and Video Compression and Transmission, which is written by leading practitioners in both fields, is one of the first references that addresses this approach and serves as an excellent information source for both researchers and practicing engineers.
    Note: 1 Removal of Blocking Artifacts Using a Hierarchical Bayesian Approach -- 2 A Stochastic Technique for the Removal of Artifacts in Compressed Images and Video -- 3 Image Recovery from Compressed Video Using Multichannel Regularization -- 4 Subband Coded Image Reconstruction for Lossy Packet Networks -- 5 Video Coding Standards: Error Resilience and Concealment -- 6 Error-Resilient Standard-Compliant Video Coding -- 7 Error Concealment in Encoded Video Streams -- 8 Error Concealment for MPEG-2 Video -- 9 Combined Source-Channel Video Coding.
    In: Springer Nature eBook
    Additional Edition: Printed edition: ISBN 9781441950635
    Additional Edition: Printed edition: ISBN 9780792382980
    Additional Edition: Printed edition: ISBN 9781475765151
    Language: English
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  • 6
    UID:
    b3kat_BV043665743
    Format: xiii, 286 Seiten , Illustrationen, Diagramme
    ISBN: 9781107123526
    Note: Literaturverzeichnis: Seite 280-284
    Language: English
    Subjects: Computer Science
    RVK:
    RVK:
    Keywords: Künstliche Intelligenz ; Maschinelles Lernen ; Kognitionswissenschaft ; Mensch-Maschine-Kommunikation
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  • 7
    UID:
    almahu_9948609668102882
    Format: 1 online resource (xxi, 574 pages) : , digital, PDF file(s).
    Edition: Second edition.
    ISBN: 9781108690935 (ebook)
    Content: With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for graduate courses on machine learning and for individual reference and self-study.
    Note: Title from publisher's bibliographic system (viewed on 07 Feb 2020).
    Additional Edition: Print version: ISBN 9781108480727
    Language: English
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  • 8
    UID:
    edocfu_9961294357402883
    Format: 1 online resource (xxi, 574 pages) : , digital, PDF file(s).
    Edition: Second edition.
    ISBN: 1-108-57402-5 , 1-108-57554-4 , 1-108-69093-9
    Content: With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for graduate courses on machine learning and for individual reference and self-study.
    Note: Title from publisher's bibliographic system (viewed on 07 Feb 2020).
    Additional Edition: ISBN 1-108-48072-1
    Language: English
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  • 9
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Imprint: Springer
    UID:
    gbv_1823900348
    Format: 1 Online-Ressource(XVI, 134 p.)
    Edition: 1st ed. 2007.
    ISBN: 9783031022432
    Series Statement: Synthesis Lectures on Image, Video, and Multimedia Processing
    Content: Introduction -- Bayesian Formulation of Super-Resolution Image Reconstruction -- Low-Resolution Image Formation Models -- Motion Estimation in Super Resolution -- Estimation of High-Resolution Images -- Bayesian Inference Models in Super Resolution -- Super Resolution for Compression.
    Content: This book focuses on the super resolution of images and video. The authors’ use of the term super resolution (SR) is used to describe the process of obtaining a high resolution (HR) image, or a sequence of HR images, from a set of low resolution (LR) observations. This process has also been referred to in the literature as resolution enhancement (RE). SR has been applied primarily to spatial and temporal RE, but also to hyperspectral image enhancement. This book concentrates on motion based spatial RE, although the authors also describe motion free and hyperspectral image SR problems. Also examined is the very recent research area of SR for compression, which consists of the intentional downsampling, during pre-processing, of a video sequence to be compressed and the application of SR techniques, during post-processing, on the compressed sequence. It is clear that there is a strong interplay between the tools and techniques developed for SR and a number of other inverse problems encountered in signal processing (e.g., image restoration, motion estimation). SR techniques are being applied to a variety of fields, such as obtaining improved still images from video sequences (video printing), high definition television, high performance color Liquid Crystal Display (LCD) screens, improvement of the quality of color images taken by one CCD, video surveillance, remote sensing, and medical imaging. The authors believe that the SR/RE area has matured enough to develop a body of knowledge that can now start to provide useful and practical solutions to challenging real problems and that SR techniques can be an integral part of an image and video codec and can drive the development of new coder-decoders (codecs) and standards.
    Additional Edition: ISBN 9783031011153
    Additional Edition: ISBN 9783031033711
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783031011153
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783031033711
    Language: English
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  • 10
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Imprint: Springer
    UID:
    gbv_182390033X
    Format: 1 Online-Ressource(CXL, 12 p.)
    Edition: 1st ed. 2007.
    ISBN: 9783031022449
    Series Statement: Synthesis Lectures on Image, Video, and Multimedia Processing
    Content: Contents: Introduction -- Elements of a Video Communication System -- Joint Source-Channel Coding -- Error-Resilient Video Coding -- Channel Modeling and Channel Coding -- Internet Video Transmission -- Wireless Video Transmission -- Conclusions.
    Content: This book deals with the problem of joint source-channel video transmission, i.e., the joint optimal allocation of resources at the application layer and the other network layers, such as data rate adaptation, channel coding, power adaptation in wireless networks, quality of service (QoS) support from the network, and packet scheduling, for efficient video transmission. Real-time video communication applications, such as videoconferencing, video telephony, and on-demand video streaming, have gained increased popularity. However, a key problem in video transmission over the existing Internet and wireless networks is the incompatibility between the nature of the network conditions and the QoS requirements (in terms, for example, of bandwidth, delay, and packet loss) of real-time video applications. To deal with this incompatibility, a natural approach is to adapt the end-system to the network. The joint source-channel coding approach aims to efficiently perform content-aware cross-layer resource allocation, thus increasing the communication efficiency of multiple network layers. Our purpose in this book is to review the basic elements of the state-of-the-art approaches toward joint source-channel video transmission for wired and wireless systems. In this book, we present a general resource-distortion optimization framework, which is used throughout the book to guide our discussions on various techniques of joint source-channel video transmission. In this framework, network resources from multiple layers are assigned to each video packet according to its level of importance. It provides not only an optimization benchmark against which the performance of other sub-optimal systems can be evaluated, but also a useful tool for assessing the effectiveness of different error control components in practical system design. This book is therefore written to be accessible to researchers, expert industrial R&D engineers, and university students who are interested in the cutting edge technologies in joint source-channel video transmission. Contents: Introduction / Elements of a Video Communication System / Joint Source-Channel Coding / Error-Resilient Video Coding / Channel Modeling and Channel Coding / Internet Video Transmission / Wireless Video Transmission / Conclusions.
    Additional Edition: ISBN 9783031011160
    Additional Edition: ISBN 9783031033728
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783031011160
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783031033728
    Language: English
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