<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The microscopy images can be affected by periodic noise, resulting in quality degradation and the appearance of repetitive patterns on the micrograph. In order to effectively remove the periodic noise, a new adaptive method is proposed in this paper. The presented approach analyzes the frequency domain of the first order Haar Wavelet transform, determines the frequency regions that correspond to noise and corrects the magnitude spectrum components of the undecomposed DFT transform of the image. Experimental results are provided. </p></abstract>

The microscopy images can be affected by periodic noise, resulting in quality degradation and the appearance of repetitive patterns on the micrograph. In order to effectively remove the periodic noise, a new adaptive method is proposed in this paper. The presented approach analyzes the frequency domain of the first order Haar Wavelet transform, determines the frequency regions that correspond to noise and corrects the magnitude spectrum components of the undecomposed DFT transform of the image. Experimental results are provided.

WAVELET AND FOURIER DECOMPOSITION BASED PERIODIC NOISE REMOVAL IN MICROSCOPY IMAGES

The Scientific Bulletin of Electrical Engineering Faculty

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The microscopy images can be affected by periodic noise, resulting in quality degradation and the appearance of repetitive patterns on the micrograph. In order...

WAVELET AND FOURIER DECOMPOSITION BASED PERIODIC NOISE REMOVAL IN MICROSCOPY IMAGES

Online veröffentlicht: 11. Mai 2018

Seitenbereich: 68 - 71

DOI: https://doi.org/10.1515/sbeef-2017-0025

Schlüsselwörter
periodic/quasi-periodic noise, frequency domain filtering, Discrete Fourier Transform, Haar wavelet

© 2018

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

WAVELET AND FOURIER DECOMPOSITION BASED PERIODIC NOISE REMOVAL IN MICROSCOPY IMAGES

Online veröffentlicht: 11. Mai 2018

Seitenbereich: 68 - 71

DOI: https://doi.org/10.1515/sbeef-2017-0025

Schlüsselwörterperiodic/quasi-periodic noise, frequency domain filtering, Discrete Fourier Transform, Haar wavelet

© 2018

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
periodic/quasi-periodic noise, frequency domain filtering, Discrete Fourier Transform, Haar wavelet