The Experts below are selected from a list of 41016 Experts worldwide ranked by ideXlab platform

J Amiaux - One of the best experts on this subject based on the ideXlab platform.

  • super resolution method using sparse regularization for Point Spread Function recovery
    Astronomy and Astrophysics, 2015
    Co-Authors: F Ngole M Mboula, J L Starck, S Ronayette, K Okumura, J Amiaux
    Abstract:

    In large-scale spatial surveys, such as the forthcoming ESA Euclid mission, images may be undersampled due to the optical sensors sizes. Therefore, one may consider using a super-resolution (SR) method to recover aliased frequencies, prior to further analysis. This is particularly relevant for Point-source images, which provide direct measurements of the instrument Point-Spread Function (PSF). We introduce SPRITE, SParse Recovery of InsTrumental rEsponse, which is an SR algorithm using a sparse analysis prior. We show that such a prior provides significant improvements over existing methods, especially on low SNR PSFs.

  • Super-resolution method using sparse regularization for Point-Spread Function recovery
    Astronomy and Astrophysics - A&A, 2015
    Co-Authors: F. M. Ngolè Mboula, J L Starck, S Ronayette, K Okumura, J Amiaux
    Abstract:

    In large-scale spatial surveys, such as the forthcoming ESA Euclid mission, images may be undersampled due to the optical sensors sizes. Therefore, one may consider using a super-resolution (SR) method to recover aliased frequencies, prior to further analysis. This is particularly relevant for Point-source images, which provide direct measurements of the instrument Point-Spread Function (PSF). We introduce SParse Recovery of InsTrumental rEsponse (SPRITE), which is an SR algorithm using a sparse analysis prior. We show that such a prior provides significant improvements over existing methods, especially on low signal-to-noise ratio PSFs.

Xiaowei Zhuang - One of the best experts on this subject based on the ideXlab platform.

  • isotropic three dimensional super resolution imaging with a self bending Point Spread Function
    Nature Photonics, 2014
    Co-Authors: Joshua C Vaughan, Xiaowei Zhuang
    Abstract:

    By exploiting a self-bending Point Spread Function based on Airy beams, a three-dimensional super-resolution fluorescence imaging is realized. A three-dimensional localization precision in the range 10–15 nm was obtained at an imaging depth of 3 µm from ∼2,000 photons per localization.

  • isotropic three dimensional super resolution imaging with a self bending Point Spread Function
    Nature Photonics, 2014
    Co-Authors: Joshua C Vaughan, Xiaowei Zhuang, Shu Jia
    Abstract:

    Airy beams maintain their intensity profiles over a large propagation distance without substantial diffraction and exhibit lateral bending during propagation1,2,3,4,5. This unique property has been exploited for the micromanipulation of particles6, the generation of plasma channels7 and the guidance of plasmonic waves8, but has not been explored for high-resolution optical microscopy. Here, we introduce a self-bending Point Spread Function (SB-PSF) based on Airy beams for three-dimensional super-resolution fluorescence imaging. We designed a side-lobe-free SB-PSF and implemented a two-channel detection scheme to enable unambiguous three-dimensional localization of fluorescent molecules. The lack of diffraction and the propagation-dependent lateral bending make the SB-PSF well suited for precise three-dimensional localization of molecules over a large imaging depth. Using this method, we obtained super-resolution imaging with isotropic three-dimensional localization precision of 10–15 nm over a 3 µm imaging depth from ∼2,000 photons per localization. By exploiting a self-bending Point Spread Function based on Airy beams, a three-dimensional super-resolution fluorescence imaging is realized. A three-dimensional localization precision in the range 10–15 nm was obtained at an imaging depth of 3 µm from ∼2,000 photons per localization.

Joshua C Vaughan - One of the best experts on this subject based on the ideXlab platform.

  • isotropic three dimensional super resolution imaging with a self bending Point Spread Function
    Nature Photonics, 2014
    Co-Authors: Joshua C Vaughan, Xiaowei Zhuang
    Abstract:

    By exploiting a self-bending Point Spread Function based on Airy beams, a three-dimensional super-resolution fluorescence imaging is realized. A three-dimensional localization precision in the range 10–15 nm was obtained at an imaging depth of 3 µm from ∼2,000 photons per localization.

  • isotropic three dimensional super resolution imaging with a self bending Point Spread Function
    Nature Photonics, 2014
    Co-Authors: Joshua C Vaughan, Xiaowei Zhuang, Shu Jia
    Abstract:

    Airy beams maintain their intensity profiles over a large propagation distance without substantial diffraction and exhibit lateral bending during propagation1,2,3,4,5. This unique property has been exploited for the micromanipulation of particles6, the generation of plasma channels7 and the guidance of plasmonic waves8, but has not been explored for high-resolution optical microscopy. Here, we introduce a self-bending Point Spread Function (SB-PSF) based on Airy beams for three-dimensional super-resolution fluorescence imaging. We designed a side-lobe-free SB-PSF and implemented a two-channel detection scheme to enable unambiguous three-dimensional localization of fluorescent molecules. The lack of diffraction and the propagation-dependent lateral bending make the SB-PSF well suited for precise three-dimensional localization of molecules over a large imaging depth. Using this method, we obtained super-resolution imaging with isotropic three-dimensional localization precision of 10–15 nm over a 3 µm imaging depth from ∼2,000 photons per localization. By exploiting a self-bending Point Spread Function based on Airy beams, a three-dimensional super-resolution fluorescence imaging is realized. A three-dimensional localization precision in the range 10–15 nm was obtained at an imaging depth of 3 µm from ∼2,000 photons per localization.

K Okumura - One of the best experts on this subject based on the ideXlab platform.

  • super resolution method using sparse regularization for Point Spread Function recovery
    Astronomy and Astrophysics, 2015
    Co-Authors: F Ngole M Mboula, J L Starck, S Ronayette, K Okumura, J Amiaux
    Abstract:

    In large-scale spatial surveys, such as the forthcoming ESA Euclid mission, images may be undersampled due to the optical sensors sizes. Therefore, one may consider using a super-resolution (SR) method to recover aliased frequencies, prior to further analysis. This is particularly relevant for Point-source images, which provide direct measurements of the instrument Point-Spread Function (PSF). We introduce SPRITE, SParse Recovery of InsTrumental rEsponse, which is an SR algorithm using a sparse analysis prior. We show that such a prior provides significant improvements over existing methods, especially on low SNR PSFs.

  • Super-resolution method using sparse regularization for Point-Spread Function recovery
    Astronomy and Astrophysics - A&A, 2015
    Co-Authors: F. M. Ngolè Mboula, J L Starck, S Ronayette, K Okumura, J Amiaux
    Abstract:

    In large-scale spatial surveys, such as the forthcoming ESA Euclid mission, images may be undersampled due to the optical sensors sizes. Therefore, one may consider using a super-resolution (SR) method to recover aliased frequencies, prior to further analysis. This is particularly relevant for Point-source images, which provide direct measurements of the instrument Point-Spread Function (PSF). We introduce SParse Recovery of InsTrumental rEsponse (SPRITE), which is an SR algorithm using a sparse analysis prior. We show that such a prior provides significant improvements over existing methods, especially on low signal-to-noise ratio PSFs.

S Ronayette - One of the best experts on this subject based on the ideXlab platform.

  • super resolution method using sparse regularization for Point Spread Function recovery
    Astronomy and Astrophysics, 2015
    Co-Authors: F Ngole M Mboula, J L Starck, S Ronayette, K Okumura, J Amiaux
    Abstract:

    In large-scale spatial surveys, such as the forthcoming ESA Euclid mission, images may be undersampled due to the optical sensors sizes. Therefore, one may consider using a super-resolution (SR) method to recover aliased frequencies, prior to further analysis. This is particularly relevant for Point-source images, which provide direct measurements of the instrument Point-Spread Function (PSF). We introduce SPRITE, SParse Recovery of InsTrumental rEsponse, which is an SR algorithm using a sparse analysis prior. We show that such a prior provides significant improvements over existing methods, especially on low SNR PSFs.

  • Super-resolution method using sparse regularization for Point-Spread Function recovery
    Astronomy and Astrophysics - A&A, 2015
    Co-Authors: F. M. Ngolè Mboula, J L Starck, S Ronayette, K Okumura, J Amiaux
    Abstract:

    In large-scale spatial surveys, such as the forthcoming ESA Euclid mission, images may be undersampled due to the optical sensors sizes. Therefore, one may consider using a super-resolution (SR) method to recover aliased frequencies, prior to further analysis. This is particularly relevant for Point-source images, which provide direct measurements of the instrument Point-Spread Function (PSF). We introduce SParse Recovery of InsTrumental rEsponse (SPRITE), which is an SR algorithm using a sparse analysis prior. We show that such a prior provides significant improvements over existing methods, especially on low signal-to-noise ratio PSFs.