Image denoising with two-dimensional zero attracting LMS algorithm

In this paper, we propose a new two-dimensional (2D) zero-attracting least-mean-square (ZALMS) adaptive filter by imposing a sparsity aware l1-norm penalty term into the cost function of the 2D-LMS algorithm. Comparisons with 2D-LMS and BM3D algorithms were conducted both on sparse and non-sparse im...

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Bibliographic Details
Published inMühendislik bilimleri dergisi Vol. 25; no. 5; pp. 539 - 545
Main Authors Eleyan, Gülden, Salman, Muhammed
Format Journal Article
LanguageEnglish
Published Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 2019
Subjects
Eğitim Bilimleri
Mühendislik
Denizli
Seyrek sinyaller
Görüntü iyileştirme
LMS
Image restoration
Sparse signals
Online AccessGet full text
ISSN1300-7009
2147-5881
2147-5881
DOI10.5505/pajes.2018.06982

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Summary:In this paper, we propose a new two-dimensional (2D) zero-attracting least-mean-square (ZALMS) adaptive filter by imposing a sparsity aware l1-norm penalty term into the cost function of the 2D-LMS algorithm. Comparisons with 2D-LMS and BM3D algorithms were conducted both on sparse and non-sparse images. The carried-out simulations show that the proposed algorithm has good capabilities in updating the filter coefficients along both horizontal and vertical directions, and its performance is similar with the 2D-LMS algorithm with lower computation time. But 2D-ZALMS performs better than BM3D algorithm.
ISSN:1300-7009
2147-5881
2147-5881
DOI:10.5505/pajes.2018.06982