Blind multi-frame deconvolution by tangential iterative projections (TIP)

Wilding, Dean; Soloviev, Oleg; Pozzi, Paolo; Vdovin, Gleb; Verhaegen, Michel

doi:10.1364/oe.25.032305

Cited by 8 publications

(9 citation statements)

References 26 publications

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“…This constraint is easy to handle, but essential for the success of our proposed algorithms, where acceleration optimization mechanisms are exploited. Its effectiveness has been widely known in the literature of deconvolution, see, e.g., [25,29]. There are several approaches to this constraint, e.g., the penalty approaches using the associated distance function or its square.…”

Section: Regularization Functionsmentioning

confidence: 99%

Subpixel image reconstruction using nonuniform defocused images

Nguyen,

Soloviev,

Noom

et al. 2021

Preprint

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This paper considers the problem of reconstructing an object with high-resolution using several low-resolution images, which are degraded due to nonuniform defocus effects caused by angular misalignment of the subpixel motions. The new algorithm, indicated by the Superresolution And Nonuniform Defocus Removal (SANDR) algorithm, simultaneously performs the nonuniform defocus removal as well as the superresolution reconstruction. The SANDR algorithm combines non-sequentially the nonuniform defocus removal method recently developed by Thao et al. and the least squares approach for subpixel image reconstruction. Hence, it inherits global convergence from its two component techniques and avoids the typical error amplification of multi-step optimization contributing to its robustness. Further, existing acceleration techniques for optimization have been proposed that assure fast convergence of the SANDR algorithm going from rate O(1/k) to O(1/k 2 ) compared to most existing superresolution (SR) techniques using the gradient descent method. An

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Section: Regularization Functionsmentioning

confidence: 99%

Subpixel image reconstruction using nonuniform defocused images

Nguyen,

Soloviev,

Noom

et al. 2021

Preprint

Self Cite

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“…5 The use of postprocessing can only recover information lost through aberrations if it is present in a set of diverse observations, either by acquiring the data from different angles, or by intentional modification of the pupil as explain in the authors previous work. 6,7 In the presence of these phase aberrations, the excitation profile of the LSFM is distorted and this strongly affects the observed fluorescence independent of what correction done on the detection path. In order to have images that do not misrepresent the fluorophore distribution, one should correct the aberrations in both the excitation and the detection light.…”

Section: Light-sheet Fluorescence Microscopy (Lsfm)mentioning

confidence: 99%

Hybrid adaptive and computational light-sheet fluorescence microscopy

Wilding

Pozzi

Soloviev

et al. 2018

Adaptive Optics and Wavefront Control for Biological Systems IV

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The light-sheet fluorescence microscopy is an excellent tool for the investigation of large three dimensional microscopy samples at the cellular level, however, the ability to resolve features is strongly affected by the presence of scattering and aberrations. These effects are two fold in light-sheet microscopy, as the illumination path providing the optical sectioning and the fluorescence detection path are both affected by the aberrations in different ways. To overcome these difficulties, we have developed hybrid adaptive optical and computational microscopy techniques to remove the effect of the aberrations in both the excitation and the fluorescence paths of these microscopes.

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“…The algorithm that is employed is a modification of the author's previous work to work with coherent imaging, it is called TIP. 3 It is demonstrated in experiment that within a couple of seconds it is possible to make a significant improvement to the PSF.…”

Section: Introductionmentioning

confidence: 98%

Rapid identification of coherent pupil functions from multiple intensity measurements

Wilding¹,

Iongh²,

Soloviev³

et al. 2017

Optical Coherence Imaging Techniques and Imaging in Scattering Media II

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By taking multiple input-output measurements, it is shown how to determine the input to an optical system that corrects unknown phase aberrations without interferometric measurements or online iterative optimization within a couple of seconds. It is shown to work in simulations and experiment. This technique may also be used to acquire the complex field in the pupil, hereby permitting a complex field image to be acquired.

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Blind multi-frame deconvolution by tangential iterative projections (TIP)

Cited by 8 publications

References 26 publications

Subpixel image reconstruction using nonuniform defocused images

Subpixel image reconstruction using nonuniform defocused images

Hybrid adaptive and computational light-sheet fluorescence microscopy

Rapid identification of coherent pupil functions from multiple intensity measurements

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