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Extraction method and denoising performance analysis of diffuse spots and silhouettes in STORM
T. Cheng1,2*, D. Hu1

1School of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, 268 Avenue Dong Huan, Chengzhong District, Liuzhou 545006, P. R. China;
2School of Artificial Intelligence, Guangxi Science and Technology Normal University, 966 Tiebei Avenue, Laibin 546199, P. R. China;
* Corresponding author

  Полный текст (PDF)

DOI: 10.18287/COJ1732

ID статьи: 1732

Аннотация:
In super-resolution microscopy based on STORM (Stochastic Optical Reconstruction Microscopy), due to the diffraction phenomenon, photons emitted by fluorescent molecules form into diffuse spots in a raw image. The regions without diffuse spots in the raw image are referred to as silhouettes. The diffuse spot regions are crucial for assessing the quality of a raw image and achieving super-resolution imaging as conventional holistic evaluation methods, which fail to distinguish between diffuse spots and silhouettes, cannot reflect the quality of the diffuse spot regions. A mask-based image segmentation algorithm is proposed here to extract and separate the diffuse spots and silhouette regions. Through simulation experiments, the denoising characteristics of three-dimensional block matching filtering (BM3D) and wide spectrum denoising (WSD) in different regions under various noise levels are compared and analyzed, and important criteria for selecting denoising methods for raw images are provided. Experiments show that better denoising is achieved with WSD than BM3D in the diffuse spot regions, while BM3D performs better in the silhouette regions in low noise level.

Ключевые слова:
super-resolution microscopy; raw image; diffuse spots; silhouette; denoising.

Благодарности:
The work was funded by Guangxi National Natural Science Foundation (2022GXNSFAA035593), National Natural Science Foundation of China (81660296, 41461082).

Citation:
Cheng T, Hu D. Extraction method and denoising performance analysis of diffuse spots and silhouettes in STORM. Computer Optics 2026; 50(4): 1732. doi:10.18287/COJ1732.

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