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Proceedings Paper

Pyramidal Normalization Filter: Visual Model With Applications To Image Understanding
Author(s): P. S. Schenker; D. R. Unangst; T. F. Knaak; D. T. Huntley; W. R. Patterson
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Paper Abstract

This paper introduces a new nonlinear filter model which has applications in low-level machine vision. We show that this model, which we designate the normalization filter, is the basis for non-directional, multiple spatial frequency channel resolved detection of image edge structure. We show that the results obtained in this procedure are in close correspondence to the zero-crossing sets of the Marr-Hildreth edge detector.6 By comparison to their model, ours has the additional feature of constant-contrast thresholding, viz., it is spatially brightness adaptive. We describe a highly efficient and flexible realization of the normalization filter based on Burt's algorithm for pyramidal filtering.18 We present illustrative experimental results that we have obtained with a computer implementation of this filter design.

Paper Details

Date Published: 28 December 1982
PDF: 10 pages
Proc. SPIE 0341, Real-Time Signal Processing V, (28 December 1982); doi: 10.1117/12.933701
Show Author Affiliations
P. S. Schenker, Brown University (United States)
D. R. Unangst, Brown University (United States)
T. F. Knaak, Brown University (United States)
D. T. Huntley, Brown University (United States)
W. R. Patterson, Brown University (United States)

Published in SPIE Proceedings Vol. 0341:
Real-Time Signal Processing V
Joel Trimble, Editor(s)

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