Echocardiographic image denoising using extreme total variation bilateral filter
| Autor: | Nagashettappa Biradar, Manojkumar Rohit, M. L. Dewal, Ishan Jindal |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
business.industry Image quality Noise reduction 0206 medical engineering Speckle noise Pattern recognition 02 engineering and technology Filter (signal processing) 020601 biomedical engineering Atomic and Molecular Physics and Optics Electronic Optical and Magnetic Materials Reduction (complexity) Metric (mathematics) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Bilateral filter Artificial intelligence Electrical and Electronic Engineering business |
| Zdroj: | Optik. 127:30-38 |
| ISSN: | 0030-4026 |
| DOI: | 10.1016/j.ijleo.2015.08.207 |
| Popis: | The transthoracic echocardiographic (TTE) images used to assess cardiac health are inherent with speckle noise, making it very difficult for accurate abnormality diagnosis. To address this issue, a novel speckle reduction known as extreme total variation bilateral (ETVB) filter is proposed in this paper. The regularizer term of total variation (TV) method is replaced with the bilateral (BL) term in the proposed ETVB filter along with the prior term. The true information is incorporated in the algorithm using Bayesian inference and probability density function. Applications of gradient projection based restoration methods are also analyzed for speckle noise reduction. Denoising characteristics are evaluated in terms of 15 image quality metrics along with visual quality. The performance of proposed ETVB filter is compared with 30 existing despeckling techniques. Exhaustive result analysis reveals that the proposed ETVB filter is superior in terms of edge and texture preservation. The focal points of result analysis are edge, structure and texture preservation along with visual outlook. Edge and structure preservation are measured using beta metric, figure of merit and structure similarity index. The values of β, FoM and SSIM are markedly enhanced using proposed filtering scheme in comparison to other total variation based methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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