@inbook{5081e9e611604a6c9620aa972eb0e7a2,

title = "Directly invertible nonlinear divisive normalization pyramid for image representation",

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.",

author = "Roberto Valerio and Simoncelli, {Eero P.} and Rafael Navarro",

note = "Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",

year = "2003",

doi = "10.1007/978-3-540-39798-4_42",

language = "English (US)",

isbn = "3540200819",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "331--340",

editor = "Narciso Garcia and Luis Salgado and Martinez, {Jose M.}",

booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}