Separable-denominator two-dimensional adaptive filters with application to noise reduction in images

Masayuki Kawamata; Eiichiro Kawakami; Tatsuo Higuchi

doi:10.1016/0096-3003(94)00102-A

Separable-denominator two-dimensional adaptive filters with application to noise reduction in images

Masayuki Kawamata, Eiichiro Kawakami, Tatsuo Higuchi

ENG - Electronic Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper, separable-denominator two-dimensional (SD-2D) adaptive filters are realized in the lattice-form and in the direct-form. The stability test for these SD-2D adaptive filters can be simplified to that for one-dimensional (1D) recursive filters. It is shown by the experiments of the noise reduction in images that the SD-2D adaptive filters are superior to the nonadaptive SD-2D filters.

Original language	English
Pages (from-to)	111-122
Number of pages	12
Journal	Applied Mathematics and Computation
Volume	69
Issue number	1
DOIs	https://doi.org/10.1016/0096-3003(94)00102-A
Publication status	Published - 1995 Apr

ASJC Scopus subject areas

Computational Mathematics
Applied Mathematics

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10.1016/0096-3003(94)00102-A

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abstract = "In this paper, separable-denominator two-dimensional (SD-2D) adaptive filters are realized in the lattice-form and in the direct-form. The stability test for these SD-2D adaptive filters can be simplified to that for one-dimensional (1D) recursive filters. It is shown by the experiments of the noise reduction in images that the SD-2D adaptive filters are superior to the nonadaptive SD-2D filters.",

author = "Masayuki Kawamata and Eiichiro Kawakami and Tatsuo Higuchi",

year = "1995",

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AU - Higuchi, Tatsuo

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AB - In this paper, separable-denominator two-dimensional (SD-2D) adaptive filters are realized in the lattice-form and in the direct-form. The stability test for these SD-2D adaptive filters can be simplified to that for one-dimensional (1D) recursive filters. It is shown by the experiments of the noise reduction in images that the SD-2D adaptive filters are superior to the nonadaptive SD-2D filters.

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ER -

Separable-denominator two-dimensional adaptive filters with application to noise reduction in images

Abstract

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