Improving the quality of low SNR images using high SNR images
- Published
- Accepted
- Subject Areas
- Computer Vision, Visual Analytics
- Keywords
- Signal-Noise-Ratio, Image Processing, Transplant, Filtering
- Copyright
- © 2019 Xie
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2019. Improving the quality of low SNR images using high SNR images. PeerJ Preprints 7:e27800v1 https://doi.org/10.7287/peerj.preprints.27800v1
Abstract
It is important to get data with Signal-Noise-Ratios (SNR) as high as possible. Compared to other techniques, filtering methods are fast. But they do not make full use of the characteristics of sample structure which reflected by relevant high SNR images. In this study, we propose a technique termed “TransFiltering”. It transplants the characteristics of a high SNR image to the frequency spectrum of a low SNR image by filtering. Usually, the high SNR and the low SNR image should have similar structure pattern. For example, they all come from the same image sequence. In the proposed method, Fourier transform is first performed on both of the images. Then, the frequency spectrum of the low SNR image is filtered according to that of the high SNR image. Finally, inverse Fourier transform is performed to get the image with improved SNR. Experiment results show that the proposed method is both effective and efficient.
Author Comment
This is a preprint submission to PeerJ Preprints.