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Proceedings Paper

Efficient image representations and features
Author(s): Michael Dorr; Eleonora Vig; Erhardt Barth
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Paper Abstract

Interdisciplinary research in human vision and electronic imaging has greatly contributed to the current state of the art in imaging technologies. Image compression and image quality are prominent examples and the progress made in these areas relies on a better understanding of what natural images are and how they are perceived by the human visual system. A key research question has been: given the (statistical) properties of natural images, what are the most efficient and perceptually relevant image representations, what are the most prominent and descriptive features of images and videos? We give an overview of how these topics have evolved over the 25 years of HVEI conferences and how they have influenced the current state of the art. There are a number of striking parallels between human vision and electronic imaging. The retina does lateral inhibition, one of the early coders was using a Laplacian pyramid; primary visual cortical areas have orientation- and frequency-selective neurons, the current JPEG standard defines similar wavelet transforms; the brain uses a sparse code, engineers are currently excited about sparse coding and compressed sensing. Some of this has indeed happened at the HVEI conferences and we would like to distill that.

Paper Details

Date Published: 14 March 2013
PDF: 9 pages
Proc. SPIE 8651, Human Vision and Electronic Imaging XVIII, 86510R (14 March 2013); doi: 10.1117/12.2002300
Show Author Affiliations
Michael Dorr, Harvard Medical School (United States)
Eleonora Vig, Harvard Univ. (United States)
Erhardt Barth, Univ. of Lübeck (Germany)


Published in SPIE Proceedings Vol. 8651:
Human Vision and Electronic Imaging XVIII
Bernice E. Rogowitz; Thrasyvoulos N. Pappas; Huib de Ridder, Editor(s)

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