Image Deblurring Using Derivative Compressed Sensing for Optical Imaging Application
Mohammad Rostami, Oleg Michailovich, Zhou Wang

TL;DR
This paper introduces a simplified, cost-effective Shack-Hartmann interferometer and a derivative compressed sensing approach to recover phase information for optical image deblurring, achieving high-quality reconstructions from limited data.
Contribution
It presents a novel, simplified interferometer design and a derivative compressed sensing method for phase recovery in optical imaging, improving accessibility and performance.
Findings
Simplified Shack-Hartmann interferometer reduces costs.
Numerical experiments show comparable image quality to dense sampling.
Effective phase recovery enables accurate image deblurring.
Abstract
Reconstruction of multidimensional signals from the samples of their partial derivatives is known to be a standard problem in inverse theory. Such and similar problems routinely arise in numerous areas of applied sciences, including optical imaging, laser interferometry, computer vision, remote sensing and control. Though being ill-posed in nature, the above problem can be solved in a unique and stable manner, provided proper regularization and relevant boundary conditions. In this paper, however, a more challenging setup is addressed, in which one has to recover an image of interest from its noisy and blurry version, while the only information available about the imaging system at hand is the amplitude of the generalized pupil function (GPF) along with partial observations of the gradient of GPF's phase. In this case, the phase-related information is collected using a simplified…
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