Отрывок: Each frame contains 34 fluorescent molecules. Poisson noise and Gaussian noise (Gaussian noise variances of 0.01) are added to each frame of the raw image. The y axis is labeled in SNR (dB). The x axis is labeled in block size The middle row is the super-resolution image re- constructed by CS based on the raw image before and after denoising and the true super-resolution image. After denoising, SSIM increased from 0.011 to 0....
Название : Super-resolution microscopy based on wide spectrum denoising and compressed sensing
Авторы/Редакторы : Cheng, T.
Jin, H.
Ключевые слова : fluorescence microscopy
super-resolution
noise
diffraction theory
compressed sensing
Дата публикации : Июн-2023
Издательство : Самарский национальный исследовательский университет
Библиографическое описание : Cheng, T. Super-resolution microscopy based on wide spectrum denoising and compressed sensing / T. Cheng, H. Jin //Computer Optics. - 2023. - Vol. 47(3). - P. 426-432. - DOI: 10.18287/2412-6179-CO-1172.
Серия/номер : 47;3
Аннотация : 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.
URI (Унифицированный идентификатор ресурса) : https://dx.doi.org/10.18287/2412-6179-CO-1172
http://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/Superresolution-microscopy-based-on-wide-spectrum-denoising-and-compressed-sensing-103216
Другие идентификаторы : Dspace\SGAU\20230424\103216
Располагается в коллекциях: Журнал "Компьютерная оптика"

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