The problem of reconstruction of digital images from their blurred and noisy measurements
is unarguably one of the central problems in imaging sciences. Despite its ill-posed nature …

ABSTRACT The Shack–Hartmann wavefront sensor is widely used to measure aberrations
induced by atmospheric turbulence in adaptive optics systems. However, if strong …

Long-time integration is an effective method for improving the signal–to–noise ratio (SNR) of
an echo. However, if the target radar cross-section (RCS) fluctuates over the long integration …

We report on an algorithm for fast wavefront sensing that incorporates sparse representation
for the first time in practice. The partial derivatives of optical wavefronts were sampled …

We propose a sparse scanning Hartmann wavefront sensor (SS-HWFS), which decouples
the dynamic range and spatial resolution that used to be traded off in a conventional HWFS …

Surface reconstruction from measurements of spatial gradient is an important computer
vision problem with applications in photometric stereo and shape-from-shading. In the case …

Compressed sensing leverages the sparsity of signals to reduce the amount of
measurements required for its reconstruction. The Shack-Hartmann wavefront sensor …

Surface reconstruction from measurements of spatial gradient is an important computer
vision problem with applications in photometric stereo and shape-from-shading. In the case …

This paper deals with the interferometric synthetic aperture radar (InSAR) phase unwrapping
problem. The proposed appraoch is based on the relationship between the gradient vectors …

In the literature the problem of compressed sensing in the presence of side information is
studied. But, in most cases the side information are about the source itself, ie structure …