The Multi-Scale Veto Model: A Two-Stage Analog Network for Edge Detection and Image Reconstruction

dc.creator	Dron, Lisa
dc.date	2004-10-04T14:25:21Z
dc.date	2004-10-04T14:25:21Z
dc.date	1992-03-01
dc.date.accessioned	2013-10-09T02:42:11Z
dc.date.available	2013-10-09T02:42:11Z
dc.date.issued	2013-10-09
dc.identifier	AIM-1320
dc.identifier	http://hdl.handle.net/1721.1/5981
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description	This paper presents the theory behind a model for a two-stage analog network for edge detection and image reconstruction to be implemented in VLSI. Edges are detected in the first stage using the multi-scale veto rule, which eliminates candidates that do not pass a threshold test at each of a set of different spatial scales. The image is reconstructed in the second stage from the brightness values adjacent to edge locations. The MSV rule allows good localization and efficient noise removal. Since the reconstructed images are visually similar to the originals, the possibility exists of achieving significant bandwidth compression.
dc.format	27 p.
dc.format	2710072 bytes
dc.format	2131529 bytes
dc.format	application/postscript
dc.format	application/pdf
dc.language	en_US
dc.relation	AIM-1320
dc.subject	edge detection
dc.subject	image reconstruction
dc.subject	analog VLSI
dc.subject	bandwidthscompression
dc.title	The Multi-Scale Veto Model: A Two-Stage Analog Network for Edge Detection and Image Reconstruction

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