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Reseach Article
Genetic Algorithm and Fisher Discriminant Analysis based Wavelet Thresholding for Speckle Noise Filtering in Ultrasound Images
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 174 - Number 30 |
| Year of Publication: 2021 |
| Authors: Shisir Mia, Md. Mahfuz Reza, Mohammad Motiur Rahman |
10.5120/ijca2021921231
|
Shisir Mia, Md. Mahfuz Reza, Mohammad Motiur Rahman . Genetic Algorithm and Fisher Discriminant Analysis based Wavelet Thresholding for Speckle Noise Filtering in Ultrasound Images. International Journal of Computer Applications. 174, 30 ( Apr 2021), 13-18. DOI=10.5120/ijca2021921231
Abstract
Speckle noise is a significant property of medical ultrasound imaging, and it typically degrades the resolution and contrast of images, sinking the diagnostic importance of the imaging modality. As a consequence, filtering speckle noise in the ultrasound images is a critical step for further analysis by the medical experts. In this paper, a speckle noise filtering technique have been suggested via wavelet thresholding for denosing ultrasound images. For each wavelet coefficient, in the first step, two optimal threshold parameters are estimated through the genetic algorithm and fisher discriminant analysis respectively. In the second step, thresholding of wavelet coefficient is performed by both threshold parameters. Finally, thresholded coefficient which corresponds to lowest mean square error is selected for obtaining the denoised ultrasound image. Results show that, the proposed technique outperforms different existing denoising techniques.
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