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01-11-2018 | Image & Signal Processing

Denoising Brain Images with the Aid of Discrete Wavelet Transform and Monarch Butterfly Optimization with Different Noises

Authors: T. E. Aravindan, R. Seshasayanan

Published in: Journal of Medical Systems | Issue 11/2018

Abstract

The aim of this paper is to denoise the high noise density image proficiently with minimal computation cost using various techniques. This paper proposes an approach for image denoising based on Discrete Wavelet Transform (DWT) in association with Monarch Butterfly Optimization (MBO) technique. Along with Gaussian noise, salt & pepper and speckle noise are added to the image and DWT is applied on the noisy image. The Haar wavelet is used to segregate the sub bands and threshold operation is carried out in three bands. The wavelet coefficient optimization process is performed for optimizing the coefficient value with the assistance of MBO technique. In this wavelet-optimized parameter, the inverse DWT (IDWT) is applied. The proposed method decreases the noise from images more efficiently. The result exhibits that MBO technique is better than the existing and other traditional techniques as it minimize the mean square error (MSE). This process is validated with PSNR value and implemented in MATLAB.

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Title: Denoising Brain Images with the Aid of Discrete Wavelet Transform and Monarch Butterfly Optimization with Different Noises
Authors: T. E. Aravindan
R. Seshasayanan
Publication date: 01-11-2018
Publisher: Springer US
Published in: Journal of Medical Systems / Issue 11/2018
Print ISSN: 0148-5598
Electronic ISSN: 1573-689X
DOI: https://doi.org/10.1007/s10916-018-1069-4

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Denoising Brain Images with the Aid of Discrete Wavelet Transform and Monarch Butterfly Optimization with Different Noises

Abstract

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