Template model for blur coding: the role of early nonlinearity in edge segmentation

Barbieri-Hesse, Gillian S. and Georgeson, Mark A. (2002). Template model for blur coding: the role of early nonlinearity in edge segmentation. IN: 25th European Conference on Visual Perception. 2002-08-25 - 2002-08-29. (Unpublished)

Abstract

We describe a template model for perception of edge blur and identify a crucial early nonlinearity in this process. The main principle is to spatially filter the edge image to produce a 'signature', and then find which of a set of templates best fits that signature. Psychophysical blur-matching data strongly support the use of a second-derivative signature, coupled to Gaussian first-derivative templates. The spatial scale of the best-fitting template signals the edge blur. This model predicts blur-matching data accurately for a wide variety of Gaussian and non-Gaussian edges, but it suffers a bias when edges of opposite sign come close together in sine-wave gratings and other periodic images. This anomaly suggests a second general principle: the region of an image that 'belongs' to a given edge should have a consistent sign or direction of luminance gradient. Segmentation of the gradient profile into regions of common sign is achieved by implementing the second-derivative 'signature' operator as two first-derivative operators separated by a half-wave rectifier. This multiscale system of nonlinear filters predicts perceived blur accurately for periodic and aperiodic waveforms. We also outline its extension to 2-D images and infer the 2-D shape of the receptive fields.

Divisions: Life & Health Sciences > Optometry
Additional Information: Abstract published in ECVP 2002 Abstract Supplement, Perception, (August 2002, 1990) 13 (Supplement), p.54, 0301-0066.
Event Title: 25th European Conference on Visual Perception
Event Type: Other
Event Dates: 2002-08-25 - 2002-08-29
Uncontrolled Keywords: perception,edge blur,early nonlinearity,spatially filter,blur-matching data,second-derivative signature,Gaussian first-derivative templates,Gaussian edges,non-Gaussian edges,receptive fields
["eprint_fieldopt_dates_date_type_" not defined] Date: 2002
Authors: Barbieri-Hesse, Gillian S.
Georgeson, Mark A. ( 0000-0002-8173-9522)

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