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Rafael Navarro - One of the best experts on this subject based on the ideXlab platform.

  • directly invertible nonlinear divisive normalization pyramid for image representation
    Lecture Notes in Computer Science, 2003
    Co-Authors: Roberto Valerio, Eero P Simoncelli, Rafael Navarro
    Abstract:

    We present a multiscale nonlinear image representation that permits an efficient coding of natural images. The input image is first decomposed into a set of subbands at multiple scales and Orientations using near-orthogonal symmetric quadrature mirror filters. This is followed by a nonlinear “divisive normalization” stage, in which each linear coefficient is divided by a value computed from a small set of neighboring coefficients in Space, Orientation and scale. This neighborhood is chosen to allow this nonlinear operation to be efficiently inverted. The parameters of the normalization operation are optimized in order to maximize the independence of the normalized responses for natural images. We demonstrate the near-independence of these nonlinear responses, and suggest a number of applications for which this representation should be well suited.

Roberto Valerio - One of the best experts on this subject based on the ideXlab platform.

  • directly invertible nonlinear divisive normalization pyramid for image representation
    Lecture Notes in Computer Science, 2003
    Co-Authors: Roberto Valerio, Eero P Simoncelli, Rafael Navarro
    Abstract:

    We present a multiscale nonlinear image representation that permits an efficient coding of natural images. The input image is first decomposed into a set of subbands at multiple scales and Orientations using near-orthogonal symmetric quadrature mirror filters. This is followed by a nonlinear “divisive normalization” stage, in which each linear coefficient is divided by a value computed from a small set of neighboring coefficients in Space, Orientation and scale. This neighborhood is chosen to allow this nonlinear operation to be efficiently inverted. The parameters of the normalization operation are optimized in order to maximize the independence of the normalized responses for natural images. We demonstrate the near-independence of these nonlinear responses, and suggest a number of applications for which this representation should be well suited.

Eero P Simoncelli - One of the best experts on this subject based on the ideXlab platform.

  • directly invertible nonlinear divisive normalization pyramid for image representation
    Lecture Notes in Computer Science, 2003
    Co-Authors: Roberto Valerio, Eero P Simoncelli, Rafael Navarro
    Abstract:

    We present a multiscale nonlinear image representation that permits an efficient coding of natural images. The input image is first decomposed into a set of subbands at multiple scales and Orientations using near-orthogonal symmetric quadrature mirror filters. This is followed by a nonlinear “divisive normalization” stage, in which each linear coefficient is divided by a value computed from a small set of neighboring coefficients in Space, Orientation and scale. This neighborhood is chosen to allow this nonlinear operation to be efficiently inverted. The parameters of the normalization operation are optimized in order to maximize the independence of the normalized responses for natural images. We demonstrate the near-independence of these nonlinear responses, and suggest a number of applications for which this representation should be well suited.

Navarro Rafael - One of the best experts on this subject based on the ideXlab platform.

  • Directly invertible nonlinear divisive normalization pyramid for image representation
    'Springer Science and Business Media LLC', 2013
    Co-Authors: Valerio R., Simoncelli E. P., Navarro Rafael
    Abstract:

    We present a multiscale nonlinear image representation that permits an efficient coding of natural images. The input image is first decomposed into a set of subbands at multiple scales and Orientations using near-orthogonal symmetric quadrature mirror filters. This is followed by a nonlinear >divisive normalization> stage, in which each linear coefficient is divided by a value computed from a small set of neighboring coefficients in Space, Orientation and scale. This neighborhood is chosen to allow this nonlinear operation to be efficiently inverted. The parameters of the normalization operation are optimized in order to maximize the independence of the normalized responses for natural images. We demonstrate the near-independence of these nonlinear responses, and suggest a number of applications for which this representation should be well suited. © Springer-Verlag Berlin Heidelberg 2003.Peer Reviewe

Valerio R. - One of the best experts on this subject based on the ideXlab platform.

  • Directly invertible nonlinear divisive normalization pyramid for image representation
    'Springer Science and Business Media LLC', 2013
    Co-Authors: Valerio R., Simoncelli E. P., Navarro Rafael
    Abstract:

    We present a multiscale nonlinear image representation that permits an efficient coding of natural images. The input image is first decomposed into a set of subbands at multiple scales and Orientations using near-orthogonal symmetric quadrature mirror filters. This is followed by a nonlinear >divisive normalization> stage, in which each linear coefficient is divided by a value computed from a small set of neighboring coefficients in Space, Orientation and scale. This neighborhood is chosen to allow this nonlinear operation to be efficiently inverted. The parameters of the normalization operation are optimized in order to maximize the independence of the normalized responses for natural images. We demonstrate the near-independence of these nonlinear responses, and suggest a number of applications for which this representation should be well suited. © Springer-Verlag Berlin Heidelberg 2003.Peer Reviewe