Multiframe blind deconvolution applied to diverse shift-and-add images of an astronomical object

Kuwamura, Susumu; Azuma, Yasuyuki; Miura, Noriaki; Tsumuraya, Fumiaki; Sakamoto, Makoto; Baba, Naoshi

doi:10.1007/s10043-014-0003-3

Cited by 4 publications

(2 citation statements)

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“…Here, we ignore motion blur. Postprocessing techniques such a multi-frame blind deconvolution [25][26][27][28] may be used to recover a near-perfect image. This approach is particularly suitable in cases where it is not practical to make repeated measurement of time varying PSF.…”

Section: Basics Of Randomized Aperture Imagingmentioning

confidence: 99%

“…Solutions to Eq.18 are commonly solved using either: (1) batch mode optimization using the constrained conjugate gradient descent of cost function with respect to f and {h n } in an alternating manner [25,28,30]; and (2) serial mode optimization using the multiplicative updates [26,31], as is shown in the method we employed, outlined below in Algorithm 1,estimated image and PSF are updated respectively using multiplicative method in each iteration:…”

Section: System Estimation and Image Recoverymentioning

confidence: 99%

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Randomized Aperture Imaging

Peng,

Ruane,

Swartzlander

2016

Preprint

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Speckled images of a binary broad band light source (600-670 nm), generated by randomized reflections or transmissions, were used to reconstruct a binary image by use of multi-frame blind deconvolution algorithms. Craft store glitter was used as reflective elements. Another experiment used perforated foil. Also reported here are numerical models that afforded controlled tip-tilt and piston aberrations. These results suggest the potential importance of a poorly figured, randomly varying segmented imaging system.

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Section: Basics Of Randomized Aperture Imagingmentioning

confidence: 99%