Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2023Image denoising in acoustic microscopy using block-matching and 4D filter18citations
  • 2023Automated tilt compensation in acoustic microscopy5citations
  • 2022Image denoising in acoustic field microscopycitations

Places of action

Chart of shared publication
Pal, Rishant
1 / 1 shared
Habib, Anowarul
3 / 10 shared
Melandsø, Frank
2 / 6 shared
Gupta, Shubham Kumar
3 / 3 shared
Kumar, Prakhar
2 / 2 shared
Melandso, Frank
1 / 1 shared
Chart of publication period
2023
2022

Co-Authors (by relevance)

  • Pal, Rishant
  • Habib, Anowarul
  • Melandsø, Frank
  • Gupta, Shubham Kumar
  • Kumar, Prakhar
  • Melandso, Frank
OrganizationsLocationPeople

document

Image denoising in acoustic field microscopy

  • Ahmad, Azeem
  • Habib, Anowarul
  • Melandso, Frank
  • Kumar, Prakhar
  • Gupta, Shubham Kumar
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.

Topics
  • impedance spectroscopy
  • scanning auger microscopy