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1156 results in Computer Graphics, Image Processing and Robotics

Page 23 of 58

  • Preface

  • Martin Vetterli, École Polytechnique Fédérale de Lausanne, Jelena Kovačević, Carnegie Mellon University, Pennsylvania, Vivek K Goyal, Boston University
  • Book:
    Foundations of Signal Processing
    Published online:
    28 May 2018
    Print publication:
    04 September 2014, pp xxv-xxviii

  • Summary

    Our main goals in this book and its companion volume, Fourier and Wavelet Signal Processing (FWSP) [57], are to enable an understanding of state-of-the-art signal processing methods and techniques, as well as to provide a solid foundation for those hoping to advance the theory and practice of signal processing. We believe that the best way to grasp and internalize the fundamental concepts in signal processing is through the geometry of Hilbert spaces, as this leverages the great innate human capacity for spatial reasoning. While using geometry should ultimately simplify the subject, the connection between signals and geometry is not innate. The reader will have to invest effort to see signals as vectors in Hilbert spaces before reaping the benefits of this view; we believe that effort to be well placed.

    Many of the results and techniques presented in the two volumes, while rooted in classic Fourier techniques for signal representation, first appeared during a flurry of activity in the 1980s and 1990s. New constructions of local Fourier transforms and orthonormal wavelet bases during that period were motivated both by theoretical interest and by applications, multimedia communications in particular. New bases with specified time – frequency behavior were found, with impact well beyond the original fields of application. Areas as diverse as computer graphics and numerical analysis embraced some of the new constructions – no surprise given the pervasive role of Fourier analysis in science and engineering.

  • 13 - Advanced Perceptual Compression

  • Gerald Friedland, Ramesh Jain, University of California, Irvine
  • Book:
    Multimedia Computing
    Published online:
    12 September 2018
    Print publication:
    28 July 2014, pp 156-173

  • Summary

    The lossy compression techniques presented so far have tried to exploit the fundamental mathematical properties of information (lossless coding), to model and approximate the properties of the signal directly (differential coding), and to model the creation of the signal (source coding, such as in speech compression). We also presented simple perceptual methods, such as the µ-law encoder.

    The methods presented in this chapter use transformations modeled after how human sensory perception works, using a much greater sophistication level. These perceptual coders are so effective that they are used in virtually every device today that handles images or sound, from photo cameras to mobile phones to DVD players to mobile digital music players.

    Before we introduce them, we recapitulate two fundamental signal transformations that are an important prerequisite for all the algorithms presented in this chapter, as well as for many of the analysis algorithms presented later. When explaining perceptual compression, two transformations are very important: the Discrete Fourier Transform (DFT) and the Discrete Cosine Transform (DCT), which are described in the following sections. Other transforms, such as the Discrete Wavelet Transforms (DWT), which are a generalization on the transforms mentioned, are also used in multimedia signal processing, and the references cited at the end of this chapter are well worth looking up.

  • Preface

  • Gerald Friedland, Ramesh Jain, University of California, Irvine
  • Book:
    Multimedia Computing
    Published online:
    12 September 2018
    Print publication:
    28 July 2014, pp xi-xii

  • Summary

    The project to write a textbook on multimedia computing started a few years ago, when the coauthors independently realized that a book that addresses the basic concepts related to the increasing volume of multimedia data in different aspects of communications in the computing age is needed.

    Digital computing started with processing numbers, but very soon after its start it began dealing with symbols of other kinds and developed computational approaches for dealing with alpha-numeric data. Efforts to use computers to deal with audio, visual, and other perceptual information did not become successful enough to be used for any applications until about the 1980s. Only slowly, computer graphics, audio processing, and visual analysis started becoming feasible. First was the ability to store large volumes of audiovisual data, then displaying or rendering it, then distributing it, and later processing and analyzing it. For that reason, it took until about the 1990s for the term multimedia to grow popular in computing.

    While different fields have emerged around acoustic, visual, and natural text content that specializes in these data types, multimedia computing deals with documents holistically, taking into account all media available. Dominated by the availability of electronic sensors, multimedia communication is currently focused on visual and audio, followed by metadata (such as GPS) and touch. Multimedia computing deals with multiple media holistically because the purpose of documents that contain multiple media is to communicate information. Information about almost all real-world events and objects must be captured using multiple sensors as each sensor only captures one aspect of the information of interest. The challenge for multimedia computing systems is to integrate the different information streams into a coherent view. Humans do this every moment of their lives from birth and are therefore often used as a baseline when building multimedia systems. Therefore it’s not surprising that, slowly but surely, all computing is becoming multimedia. The use of multimedia data in computing has grown even more rapidly than imagined just a few years ago with the installation of cameras in cell phones in combination with the ability to share multimedia documents in social networks easily.

  • 19 - Content and Context

  • Gerald Friedland, Ramesh Jain, University of California, Irvine
  • Book:
    Multimedia Computing
    Published online:
    12 September 2018
    Print publication:
    28 July 2014, pp 290-304

  • Summary

    In the previous chapters, we described many signal processing and content analysis techniques. However, the content of an image or audio file does not alone determine its meaning and impression on the user. In this chapter, we will therefore describe other factors that are very important to consider in multimedia computing: the set of surrounding circumstances in which the content is presented, otherwise known as context. Context is often neglected in academic work because it can be leveraged in many ways in multimedia systems and is often so effective that the content analysis approach becomes secondary. So let us first find out what context really is.

    Almost two centuries ago, George Berkeley asked: If a tree falls in a forest and no one is around to hear it, does it make a sound? Sound is often defined as the sensation excited in the ear when the air or other medium is set in motion. Thus, if there is no receiving ear, then there is no sound. In other words, perception is not only data – it is a close interaction between the data, transmission medium, and the interpreter. This is shown in Figure 19.1.

  • The data acquired for an environment

  • The medium used to transmit physical attributes to the perceiver

  • The perceiver

    • Characteristics of each of these must be considered in designing and developing a multimedia system. It has been very well realized, and rigorously articulated and represented, that we understand the world based on the sensory data that we receive using our sensors and the knowledge about the world that we have accumulated since our birth. Both the data and the knowledge are integral components of understanding.

  • 2 - Multimedia: A Definition

  • Gerald Friedland, Ramesh Jain, University of California, Irvine
  • Book:
    Multimedia Computing
    Published online:
    12 September 2018
    Print publication:
    28 July 2014, pp 6-14

  • Summary

    Only a few inventions in the history of civilization have had the same impact on society in so many ways and at so many levels as computers. Where once we used computers for computing with simple alphanumeric data, we now use them primarily to exchange information, to communicate, and to share experiences. Computers are rapidly evolving as a means for gaining insights and sharing ideas across distance and time.

    Multimedia computing started gaining serious attention from researchers and practitioners during the 1990s. Before 1991, people talked about multimedia, but the computing power, storage, bandwidth, and processing algorithms were not advanced enough to deal with audio and video. With the increasing availability and popularity of CDs, people became excited about creating documents that could include not only text, but also images, audio, and even video. That decade saw explosive growth in all aspects of hardware and software technology related to multimedia computing and communication. In the early 1990s, PC manufacturers labeled their high-end units containing advanced graphics multimedia PCs. That trend disappeared a few years later because every new computer became a multimedia computer.

Page 23 of 58