sCMOS Noise-Corrected Superresolution Reconstruction Algorithm for Structured Illumination Microscopy
Structured illumination microscopy (SIM) is widely applied due to its high temporal and spatial resolution imaging ability. sCMOS cameras are often used in SIM due to their superior sensitivity, resolution, field of view, and frame rates. However, the unique single-pixel-dependent readout noise of s...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Photonics |
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| Online Access: | https://www.mdpi.com/2304-6732/9/3/172 |
| _version_ | 1797443497922396160 |
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| author | Bo Zhou Xiaoshuai Huang Junchao Fan Liangyi Chen |
| author_facet | Bo Zhou Xiaoshuai Huang Junchao Fan Liangyi Chen |
| author_sort | Bo Zhou |
| collection | DOAJ |
| description | Structured illumination microscopy (SIM) is widely applied due to its high temporal and spatial resolution imaging ability. sCMOS cameras are often used in SIM due to their superior sensitivity, resolution, field of view, and frame rates. However, the unique single-pixel-dependent readout noise of sCMOS cameras may lead to SIM reconstruction artefacts and affect the accuracy of subsequent statistical analysis. We first established a nonuniform sCMOS noise model to address this issue, which incorporates the single-pixel-dependent offset, gain, and variance based on the SIM imaging process. The simulation indicates that the sCMOS pixel-dependent readout noise causes artefacts in the reconstructed SIM superresolution (SR) image. Thus, we propose a novel sCMOS noise-corrected SIM reconstruction algorithm derived from the imaging model, which can effectively suppress the sCMOS noise-related reconstruction artefacts and improve the signal-to-noise ratio (SNR). |
| first_indexed | 2024-03-09T12:56:57Z |
| format | Article |
| id | doaj.art-6e743f867db24b40b16b56404543f40b |
| institution | Directory Open Access Journal |
| issn | 2304-6732 |
| language | English |
| last_indexed | 2024-03-09T12:56:57Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Photonics |
| spelling | doaj.art-6e743f867db24b40b16b56404543f40b2023-11-30T21:59:12ZengMDPI AGPhotonics2304-67322022-03-019317210.3390/photonics9030172sCMOS Noise-Corrected Superresolution Reconstruction Algorithm for Structured Illumination MicroscopyBo Zhou0Xiaoshuai Huang1Junchao Fan2Liangyi Chen3State Key Laboratory of Membrane Biology, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, School of Future Technology, Peking University, Beijing 100871, ChinaBiomedical Engineering Department, Peking University, Beijing 100871, ChinaChongqing Key Laboratory of Image Cognition, College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaState Key Laboratory of Membrane Biology, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, School of Future Technology, Peking University, Beijing 100871, ChinaStructured illumination microscopy (SIM) is widely applied due to its high temporal and spatial resolution imaging ability. sCMOS cameras are often used in SIM due to their superior sensitivity, resolution, field of view, and frame rates. However, the unique single-pixel-dependent readout noise of sCMOS cameras may lead to SIM reconstruction artefacts and affect the accuracy of subsequent statistical analysis. We first established a nonuniform sCMOS noise model to address this issue, which incorporates the single-pixel-dependent offset, gain, and variance based on the SIM imaging process. The simulation indicates that the sCMOS pixel-dependent readout noise causes artefacts in the reconstructed SIM superresolution (SR) image. Thus, we propose a novel sCMOS noise-corrected SIM reconstruction algorithm derived from the imaging model, which can effectively suppress the sCMOS noise-related reconstruction artefacts and improve the signal-to-noise ratio (SNR).https://www.mdpi.com/2304-6732/9/3/172SIMsuperresolutionsCMOS cameranoise correction |
| spellingShingle | Bo Zhou Xiaoshuai Huang Junchao Fan Liangyi Chen sCMOS Noise-Corrected Superresolution Reconstruction Algorithm for Structured Illumination Microscopy Photonics SIM superresolution sCMOS camera noise correction |
| title | sCMOS Noise-Corrected Superresolution Reconstruction Algorithm for Structured Illumination Microscopy |
| title_full | sCMOS Noise-Corrected Superresolution Reconstruction Algorithm for Structured Illumination Microscopy |
| title_fullStr | sCMOS Noise-Corrected Superresolution Reconstruction Algorithm for Structured Illumination Microscopy |
| title_full_unstemmed | sCMOS Noise-Corrected Superresolution Reconstruction Algorithm for Structured Illumination Microscopy |
| title_short | sCMOS Noise-Corrected Superresolution Reconstruction Algorithm for Structured Illumination Microscopy |
| title_sort | scmos noise corrected superresolution reconstruction algorithm for structured illumination microscopy |
| topic | SIM superresolution sCMOS camera noise correction |
| url | https://www.mdpi.com/2304-6732/9/3/172 |
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