Improving the quality of low SNR images using high SNR images
Year: 2019
Type: preprint
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: Yaohua Xie
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4247094872