rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: 3-D Shape Estimation and Image Restoration
    sub title: Exploiting Defocus and Motion Blur
  name:
    name part: Favaro, Paolo.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Soatto, Stefano.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxk
    date issued: 2007
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIV, 249 p. online resource.
  abstract: Images contain information about the spatial properties of the scene they depict. When coupled with suitable assumptions, images can be used to infer three-dimensional information. This useful volume concentrates on motion blur and defocus, which can be exploited to infer the 3-D structure of a scene—as well as its radiance properties—and which in turn can be used to generate novel images with better quality. 3-D Shape Estimation and Image Restoration presents a coherent framework for the analysis and design of algorithms to estimate 3-D shape from defocused and motion blurred images, and to eliminate defocus and motion blur to yield "restored" images. It provides a collection of algorithms that are optimal with respect to the chosen model and estimation criterion. Topics and Features include: • Comprehensive introduction to guide readers through the different areas of the topic • Basic models of image formation • Discussion of least-squares shape from defocus • Unifying defocus and motion blur • Handling multiple moving objects • Dealing with occlusions • Appendices supply the necessary background in optimization and regularization • www.eps.hw.ac.uk/~pf21/FavaroSoattoBook/downloads contains implementations of relevant algorithms, test data and demos. Written for readers with interests in image processing and computer vision and with backgrounds in engineering, science or mathematics, this highly practical text/reference is accessible to advanced students or those with a degree that includes basic linear algebra and calculus courses. It can also be seen as a resource for practitioners looking to expand their knowledge in the subject.
  table of contents: Basic models of image formation -- Some analysis: When can 3-D shape be reconstructed from blurred images? -- Least-squares shape from defocus -- Enforcing positivity: Shape from defocus and image restoration by minimizing I-divergence -- Defocus via diffusion: Modeling and reconstruction -- Dealing with motion: Unifying defocus and motion blur -- Dealing with multiple moving objects -- Dealing with occlusions -- Final remarks.
  note: by Paolo Favaro, Stefano Soatto.
  subject:
    topic: Computer science
  subject:
    topic: Computer graphics
  subject:
    topic: Image processing
  subject:
    topic: Algorithms
  subject:
    topic: Optics
  subject:
    topic: Optoelectronics
  subject:
    topic: Plasmons (Physics)
  subject:
    topic: Computer Science
  subject:
    topic: Image Processing and Computer Vision
  subject:
    topic: Computer Imaging, Vision, Pattern Recognition and Graphics
  subject:
    topic: Algorithms
  subject:
    topic: Signal, Image and Speech Processing
  subject:
    topic: Computer Graphics
  subject:
    topic: Optics, Optoelectronics, Plasmonics and Optical Devices
  classification: TA1637-1638
  classification: TA1634
  classification: 006.6
  classification: 006.37
  related item:
    title info:
      title: Springer eBooks
  identifier: 9781846286889
  identifier: http://dx.doi.org/10.1007/978-1-84628-688-9
  record info:
    record creation date: 100301
    record change date: 20151204191742.0
    record identifier: 978-1-84628-688-9