(Enter summary)
Abstract: Several adaptive LMS L-filters, both constrained and unconstrained ones, are developed
for noise suppression in images and being compared in this paper. First, the
location-invariant LMS L-filter for a nonconstant signal corrupted by zero-mean additive
white noise is derived. It is demonstrated that the location-invariant LMS L-filter
can be described in terms of the generalized linearly constrained adaptive processing
structure proposed by Griffiths and Jim. Subsequently, the normalized and... (Update)
Context of citations to this paper: More
.... (cf. 9] On the contrary, adaptive L filters are appealing because they avoid the computational burden of the noniterative methods [10]. Recently, increasing attention has been given to nonlinear processing of vector valued signals. It is well known that there is no...
.... adaptive filtering algorithms that suppress the cumulative noise effect due to transmission channel and quantization errors [19, 20, 21], and, iv) possibly postprocessing algorithms, such as speechassisted video warping algorithms (e.g. lip synchronization) to...
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BibTeX entry: (Update)
C. Kotropoulos and I. Pitas, "Adaptive LMS L-filters for noise suppression in images", IEEE Transactions on Image Processing, vol. 5, no. 12, pp. 1596--1609, December 1996. http://citeseer.ist.psu.edu/kotropoulos96adaptive.html More
@misc{ kotropoulos96adaptive,
author = "C. Kotropoulos and I. Pitas",
title = "Adaptive LMS L-filters for noise suppression in images",
text = "C. Kotropoulos and I. Pitas, Adaptive LMS L-filters for noise suppression
in images, IEEE Transactions on Image Processing, vol. 5, no. 12, pp. 1596--1609,
December 1996.",
year = "1996",
url = "citeseer.ist.psu.edu/kotropoulos96adaptive.html" }
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