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Data Analytics in Machine Learning: New Directions and Challenges in Knowledge-Based Systems Read chapter Read first chapter

2019 | OriginalPaper | Chapter

A Novel Despeckling Approach for Ultrasound Images Using Adaptive OBNLM Filter

Authors : Bo Quoc Bao, Tong Van Luyen, Nguyen Hai Duong, Ta Chi Hieu

Published in: Advances in Engineering Research and Application

Publisher: Springer International Publishing

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Abstract

The Optimize Bayesian Non-Local Mean Filter (OBNLM) provides a very strong tool for despeckling in Ultrasound. However, some parameters of this filter depend on the input (noise) and they are difficult to adjust. This article generates a denoising solution using the adaptive OBNLM filter in combination with the Binary Bat Algorithm (BBA) and on the no-reference Q-Metric (BBA-OBNLM). The proposed filter can despeckle noise without the need for reference images and still keep the image details, edges and textures in good condition. Furthermore, in this article, we have also carried out some simulations with images which are added speckle noise with different variances to demonstrate the performance of the proposed method superior to previous publications.

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Metadata
Title
A Novel Despeckling Approach for Ultrasound Images Using Adaptive OBNLM Filter
Authors
Bo Quoc Bao
Tong Van Luyen
Nguyen Hai Duong
Ta Chi Hieu
Copyright Year
2019
Book
Advances in Engineering Research and Application

Print ISBN: 978-3-030-04791-7

Electronic ISBN: 978-3-030-04792-4

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-04792-4_12

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