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Proceedings Paper

Image filtering derived from a model of quantum-limited detection
Author(s): Peter J. Warter; Charles G. Boncelet
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Paper Abstract

This paper considers an image filter to remove small features of low contrast based on a simple model of a quantum limited detector. That is, it removes image noise that can't be seen or that, in other circumstances, can't represent real information. The filtering scheme asks how large an area can be covered with one color without introducing visible departures from the original image. We use a quad tree structure to examine progressively larger image areas until we reach a point that setting the area to one color would obscure visible image features. We have applied these algorithms to a number of grey scale images, ranging from finely detailed images of high contrast to simple classroom video scenes without much fine detail. We have seen reductions by factors from four to twelve in the number of leaf nodes in the quad tree representation of the filtered images relative to the original images. We have also experimented with the filtering of difference images from the classroom video sequence which was made with a stationary camera and have seen substantial further reductions in quad tree complexity for the difference images by factors of two to four.

Paper Details

Date Published: 1 July 1990
PDF: 9 pages
Proc. SPIE 1247, Nonlinear Image Processing, (1 July 1990); doi: 10.1117/12.19602
Show Author Affiliations
Peter J. Warter, Univ. of Delaware (United States)
Charles G. Boncelet, Univ. of Delaware (United States)


Published in SPIE Proceedings Vol. 1247:
Nonlinear Image Processing
Edward J. Delp, Editor(s)

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