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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Kočí, Jan | Prague |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Habib, Anowarul
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (10/10 displayed)
- 2024Probabilistic impact localization in composites using wavelet scattering transform and multi-output Gaussian process regressioncitations
- 2023Image inpainting in acoustic microscopycitations
- 2023Image denoising in acoustic microscopy using block-matching and 4D filtercitations
- 2023Uncertainty Quantification in Acoustic Impedance of Atlantic Salmon Fish Scale using Scanning Acoustic Microscopy
- 2023Automated tilt compensation in acoustic microscopycitations
- 2022Image denoising in acoustic field microscopy
- 2020Evaluation of adhesive-free focused high-frequency PVDF copolymer transducers fabricated on spherical cavities
- 2018Nonlocal damage mechanics for quantification of health for piezoelectric sensorcitations
- 2018High frequency copolymer ultrasonic transducer array of size-effective elements
- 2013Ultrasonic characterization and defect detection in piezoelectric materials
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document
Image denoising in acoustic field microscopy
Abstract
Scanning acoustic microscopy (SAM) has been employed since microscopic images are widely used for biomedical or materials research. Acoustic imaging is an important and well-established method used in nondestructive testing (NDT), bio-medical imaging, and structural health monitoring.The imaging is frequently carried out with signals of low amplitude, which might result in leading that are noisy and lacking in details of image information. In this work, we attempted to analyze SAM images acquired from low amplitude signals and employed a block matching filter over time domain signals to obtain a denoised image. We have compared the images with conventional filters applied over time domain signals, such as the gaussian filter, median filter, wiener filter, and total variation filter. The noted outcomes are shown in this article.