Super-resolution microscopy based on wide spectrum denoising and compressed sensing

Super-resolution microscopy based on wide spectrum denoising and compressed sensing

Автор: Cheng Tao, Jin Hu

Журнал: Компьютерная оптика @computer-optics

Рубрика: Обработка изображений, распознавание образов

Статья в выпуске: 3 т.47, 2023 года.

Бесплатный доступ

WSD can effectively remove random noise of a raw image from very low density to ultra-high density fluorescent molecular distribution scenarios. The size of the raw image that WSD can denoise is subject to the used measurement matrix. A large raw image must be divided into blocks so that WSD denoises each block separately. Based on traditional single-molecule localization and super-resolution reconstruction scenarios, wide spectrum denoising (WSD) for blocks of different sizes was studied. The denoising ability is related to block sizes. The general trend is when the block gets larger, the denoising effect gets worse. When the block size is equal to 10, the denoising effect is the best. Using compressed sensing, only 20 raw images are needed for reconstruction. The temporal resolution is less than half a second. The spatial resolution is also greatly improved.

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Fluorescence microscopy, super-resolution, noise, diffraction theory, compressed sensing

Короткий адрес: https://sciup.org/140300069

IDR: 140300069   |   DOI: 10.18287/2412-6179-CO-1172

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