Proceedings ArticleDOI
Quantitative comparison of median-based filters
T. G. Campbell,Hans du Buf +1 more
- Vol. 1360, pp 176-187
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TLDR
In this article, a test image which contains a central disk-shaped region with a step or a ramp edge against a uniform background is compared by considering a median-based filtering technique.Abstract:
Median-based filtering techniques are compared by considering a test image which contains a central disk-shaped region with a step or a ramp edge against a uniform background. Free parameters are the amplitude of Gaussian noise added the edge slope and the number of filtering iterations. The quantitative comparison measure is the normalized squared error between the filtered noisy image and the noise-free image on the fiat image regions and on the transition region separately.© (1990) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.read more
Citations
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Multiscale median and morphological filters for 2D pattern recognition
TL;DR: Experiments demonstrate a multiscale decomposition that complements those using standard linear functions and suggests that whilst some sieves produce an invertible transform, others have better statistical behaviour.
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Adaptive rank-order filters for image processing based on local anisotropy measures
TL;DR: With the aim of developing low-level adaptive rank-order filters for carrying out in a unified approach the tasks outlined above, the basic requirements to be met by these filters can be outlined as follows.
Proceedings ArticleDOI
Sieves and wavelets: multiscale transforms for pattern recognition
J.A. Bangham,T.G. Campbell +1 more
TL;DR: A scalelposition decomposition that is an alternative to wavelets is described that can represent structural information in a way that is independent of spatial frequency, has different uncertainty tradeoffs, and can be used for scale, position and contrast independent pattern recognition.
Journal ArticleDOI
Smoothing with adaptive rank order filters for early processing in image segmentation
TL;DR: In this paper, two non-linear smoothing filters based on adaptive rank order filtering are proposed to select as output a grey value that is stable with respect to the fluctuations of the local grey value distribution inside homogeneous regions, i.e. suitable for use as a region label for image segmentation purposes.