Multiscale recursive medians, scale-space, and transforms with applications to image processing

Bangham, JA, Ling, P and Young, R (1996) Multiscale recursive medians, scale-space, and transforms with applications to image processing. IEEE Transactions on Image Processing, 5 (6). pp. 1043-1048. ISSN 1057-7149

Full text not available from this repository.

Abstract

A cascade of increasing scale, 1-D, recursive median filters produces a sieve, termed an R-sieve, has a number of properties important to image processing. In particular, it (1) Simplifies signals without introducing new extrema or edges, that is, it preserves scale-space. It shares this property with Gaussian filters, but has the advantage of being significantly more robust. (2) The differences between successive stages of the sieve yield a transform, to the granularity domain. Patterns and shapes can be recognized in this domain using idempotent matched sieves and the result transformed back to the spatial domain. The R-sieve is very fast to compute and has a close relationship to 1-D alternating sequential filters with flat structuring elements. They are useful for machine vision applications

Item Type:	Article
Faculty \ School:	Faculty of Science > School of Computing Sciences
Depositing User:	Vishal Gautam
Date Deposited:	07 Mar 2011 14:37
Last Modified:	15 Dec 2022 02:04
URI:	https://ueaeprints.uea.ac.uk/id/eprint/23208
DOI:	10.1109/83.503918

Actions (login required)

View Item