Texture classification based on comparison of second-order statistics. I. Two-point probability density function estimation and distance measure

    Authors

    A. A. Goon;J. P. Rolland

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Abbreviated Journal Title

    J. Opt. Soc. Am. A-Opt. Image Sci. Vis.

    Keywords

    IMAGES; TISSUE; NOISE; Optics

    Abstract

    The two-point probability density function (2P-PDF) gives a full description of the first- and second-order statistics of a random process. We propose a framework. for texture classification based on a distance measure between 2P-PDF's after equalization of first-order statistics. This framework allows extraction of the structural information of the process independently of the dynamic range of the image. We present; two methods for estimating the 2P-PDF of texture images, and we establish some criteria for efficient computation. The theoretical framework for noise-free texture images is validated with four texture ensembles. (C) 1999 Optical Society of America [S0740-3232(99)00807-8].

    Journal Title

    Journal of the Optical Society of America a-Optics Image Science and Vision

    Volume

    16

    Issue/Number

    7

    Publication Date

    1-1-1999

    Document Type

    Article

    Language

    English

    First Page

    1566

    Last Page

    1574

    WOS Identifier

    WOS:000081223300006

    ISSN

    0740-3232

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