Multiwavelength coherent phase imaging from noisy intensity observations
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KATKOVNIK, Vladimir; SHEVKUNOV, Igor; PETROV, N.; EGIAZARIAN, K.. Multiwavelength coherent phase imaging from noisy intensity observations. In: Materials Science and Condensed Matter Physics. Ediția a 9-a, 25-28 septembrie 2018, Chișinău. Chișinău, Republica Moldova: Institutul de Fizică Aplicată, 2018, p. 288.
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Materials Science and Condensed Matter Physics
Ediția a 9-a, 2018
Conferința "International Conference on Materials Science and Condensed Matter Physics"
Chișinău, Moldova, 25-28 septembrie 2018

Multiwavelength coherent phase imaging from noisy intensity observations


CZU: 004+538.9+539.1
Pag. 288-288

Katkovnik Vladimir1, Shevkunov Igor12, Petrov N.2, Egiazarian K.1
 
1 Tampere University of Technology,
2 ITMO University
 
Disponibil în IBN: 12 februarie 2019


Rezumat

We propose novel algorithms for absolute phase retrieval from multiwavelength noisy phase coded diffraction patterns. The phase masks are applied for modulation of multiwavelength object wavefronts. The algorithm uses the forward/backward propagation for coherent light beams and sparsely encoding wavefronts which leads to the complex-domain block-matching 3D filtering. The key-element of the algorithm is an original aggregation of the multiwavelength wavefronts for reconstruction of high-dynamic-range absolute phase of the object. Two lensless optical setups are studied: Wavelength (color) Multiplexing (WM) and Wavelength (color) Division (WD). In WM, a broadband light source radiates all wavelengths (RGB in our tests) simultaneously and CMOS sensor equipped with color filter array (CFA) registers spectral measurements. In WD, separate successive experiments are produced for each of the wavelengths with the results registered by a broadband CCD sensor without CFA. The algorithms for these two setups are quite different, in particular, because the WM algorithm requires interpolation of the RGB data subsampled by CFA for pixels, where there are no observations of some of the wavebands. The WD algorithm deals with the observations obtained for all pixels for each of the RGB bands separately. The presented algorithms and approaches are based on our results published in [1]-[3]. Simulation tests demonstrate that the developed approach leads to the effective solutions explicitly using the sparsity for noise suppression and high-accuracy object absolute phase reconstruction from noisy data.