Proceedings of the International Conference on Signal Processing and Computer Vision (SIPCOV-2023)

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Image Denoising by Curvelet Transform Based Adaptive Gaussian Notch Filter

Authors
R. Praveena1, *, S. Mary Cynthia2, S. Jacily Jemila3, T. R. Ganesh Babu1
1Muthayammal Engineering College, Salem, Tamil Nadu, India
2Sri Venkateswara College of Engineering, Chennai, Tamil Nadu, India
3Saveetha University, Chennai, Tamil Nadu, India
*Corresponding author. Email: praveenajuhi@gmail.com
Corresponding Author
R. Praveena
Available Online 4 October 2024.
DOI
10.2991/978-94-6463-529-4_35How to use a DOI?
Keywords
AGNF; Curvelet; Fourier; PSNR
Abstract

In this work a new adaptive Gaussian notch filter (AGNF) with curvelet transform is proposed for removing noises from Magnetic Resonance Images. MRI images corrupted by periodic noises which are occurred because of interferences during image capturing. In general, the interferences occur due to electric or magnetic circuits. These periodic noises can be identified by repetitive patterns formed in the image. Since periodic noises affects the image quality the elimination of this noise is very important. The Adaptive Gaussian Notch filter identifies noisy peak areas and eliminates corrupted regions, also size of window is varied based on size of the noisy frequencies of the noise affected frequency domain image. This window size is varied from smaller size to the size of the noisy peak areas. The Curvelet transform having very high degree of directionality and anisotropy compared with Fourier transform and wavelet transform. In which both Fourier transform and curvelet transform were used to isolate noise regions. Finally, the calculated PSNR values were compared and the best one were identified.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Signal Processing and Computer Vision (SIPCOV-2023)
Series
Advances in Engineering Research
Publication Date
4 October 2024
ISBN
978-94-6463-529-4
ISSN
2352-5401
DOI
10.2991/978-94-6463-529-4_35How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - R. Praveena
AU  - S. Mary Cynthia
AU  - S. Jacily Jemila
AU  - T. R. Ganesh Babu
PY  - 2024
DA  - 2024/10/04
TI  - Image Denoising by Curvelet Transform Based Adaptive Gaussian Notch Filter
BT  - Proceedings of the International Conference on Signal Processing and Computer Vision (SIPCOV-2023)
PB  - Atlantis Press
SP  - 391
EP  - 400
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-529-4_35
DO  - 10.2991/978-94-6463-529-4_35
ID  - Praveena2024
ER  -