RUS  ENG
Full version
JOURNALS // Computer Optics // Archive

Computer Optics, 2023 Volume 47, Issue 4, Pages 614–619 (Mi co1162)

This article is cited in 1 paper

IMAGE PROCESSING, PATTERN RECOGNITION

Super-resolution microscopy based on interpolation and wide spectrum de-noising

T. Cheng, Ch. Tao

Guangxi University of Science and Technology, 545006, P.R. China, Liuzhou, Chengzhong District, Avenue Donghuan, 268

Abstract: In the conventional single-molecule localizations and super-resolution microscopy, the pixel size of a raw image is approximately equal to the standard deviation of the point spread function. Such a raw image is referred to herein as a conventional raw image, based on which better single molecule localization effect and efficiency can be achieved. It is found that both interpolation and de-noising can effectively improve the Signal to Noise Ratio of the conventional raw image. The conventional raw image, the de-noised, the interpolated and the de-noised interpolated are compared and analyzed and compressed sensing is used for super-resolution reconstruction. The simulation results show that both the highest Signal to Noise Ratio and the best super-resolution reconstruction can be obtained by de-noising the interpolated conventional raw image. This method also renders the best super-resolution reconstruction and minimum gradient in the real experiment. De-noising the interpolated conventional raw image is an effective method to improve the super-resolution microscopy.

Keywords: super-resolution microscopy; interpolation; de-noising; point spread function; compressed sensing

Received: 06.01.2023
Accepted: 20.02.2023

Language: English

DOI: 10.18287/2412-6179-CO-1272



© Steklov Math. Inst. of RAS, 2024