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On the Information Content along Edges in Trichromatic Images

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We introduce a theoretical framework for measuring the information content in the edges extracted from a color image. The main difficulty in estimating the amount of information (differential entropy [1, 2]) in an image signal is to fit an appropriate probability mass function to the trichromatic image data. To estimate the amount of information in the edges extracted from a color image, we first convolve the image with a derivative filter. By fitting a Kotz-Type probability distribution to the convolved image, we then estimate the differential entropy of the edge coefficients as a measure of the uncertainty involved in the edge content of a postreceptoral chromatic image. The proposed estimation of differential entropy provides an efficient means of processing the edge content information under a variety of natural illuminations, which might be further used as a quantitative measure for evaluating color constant image retrieval.
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Document Type: Research Article

Publication date: January 1, 2013

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  • CIC is the premier annual technical gathering for scientists, technologists, and engineers working in the areas of color science and systems, and their application to color imaging. Participants represent disciplines ranging from psychophysics, optical physics, image processing, color science to graphic arts, systems engineering, and hardware and software development. While a broad mix of professional interests is the hallmark of these conferences, the focus is color. CICs traditionally offer two days of short courses followed by three days of technical sessions that include three keynotes, an evening lecture, a vibrant interactive (poster) papers session, and workshops. An endearing symbol of the meeting is the Cactus Award, given each year to the author(s) of the best interactive paper; there are also Best Paper and Best Student Paper awards.

    Please note: for Purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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