Sparse superresolution phase retrieval from phase-coded noisy intensity patterns
Research output: Contribution to journal › Article › Scientific › peer-review
|Publication status||Published - 1 Sep 2017|
|Publication type||A1 Journal article-refereed|
We consider a computational superresolution inverse diffraction problem for phase retrieval from phase-coded intensity observations. The optical setup includes a thin lens and a spatial light modulator for phase coding. The designed algorithm is targeted on an optimal solution for Poissonian noisy observations. One of the essential instruments of this design is a complex-domain sparsity applied for complex-valued object (phase and amplitude) to be reconstructed. Simulation experiments demonstrate that good quality imaging can be achieved for high-level of the superresolution with a factor of 32, which means that the pixel of the reconstructed object is 32 times smaller than the sensor's pixel. This superresolution corresponds to the object pixel as small as a quarter of the wavelength.
- complex-domain sparsity, discrete optical signal processing, phase imaging, phase retrieval, superresolution