Image filtering using multiresolution representations
Ranganath, S.
Philips Lab., Briarcliff Manor, NY;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: May 1991
Volume: 13,
Issue: 5
On page(s): 426-440
ISSN: 0162-8828
References Cited: 23
CODEN: ITPIDJ
INSPEC Accession Number: 3971423
Digital Object Identifier: 10.1109/34.134042
Current Version Published: 2002-08-06
Abstract
It is shown how multiresolution representations can be used for
filter design and implementation. These representations provide a coarse
frequency decomposition of the image, which forms the basis for two
filtering techniques. The first method, based on image pyramids, is used
for approximating the convolution of an image with a given mask. In this
technique, a filter is designed using a least-squares procedure based on
filters synthesized from the basic pyramid equivalent filters. The
second method is an adaptive noise reduction algorithm. An optimally
filtered image is synthesized from the multiresolution levels, which in
this case are maintained at the original sampling density. Individual
pixels of the image representation are linearly combined under a minimum
mean square error criterion. This uses a local signal-to-noise ratio
estimate to provide the best compromise between noise removal and
resolution loss
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