Experimental evidence for spatial stabilization of deep-turbulence-induced anisoplanatic blur.

We present field-experiment support for the feasibility of post-detection restoration when imaging through deep turbulence characterized by extreme anisoplanatism. Short-exposure images of point-like and minimally extended objects (MEOs) were collected, viewed through a 5.1-kilometer atmospheric path producing isoplanatic angles roughly 1/15th the camera diffraction-limited angular resolution. A correlation-based isoplanatic angle measurement technique is presented along with data verifying deep-turbulence conditions. In agreement with prior wave-optics simulations, the experiments demonstrate short-exposure images of MEOs retain a central lobe that is clearly narrower than the long-exposure counterpart, even in the presence of severe anisoplanatism. New simulations are presented to provide direct comparison with measurements of point-like and MEO image central lobe radius statistics.

Silhouette estimation.

Silhouettes arise in a variety of imaging scenarios. Pristine silhouettes are often degraded via blurring, detector sampling, and detector noise. We present a maximum a posteriori estimator for the restoration of parameterized facial silhouettes. Extreme dealiasing and dramatic superresolution, well beyond the diffraction limit, are demonstrated through the use of strong prior knowledge.

Overcoming turbulence-induced space-variant blur by using phase-diverse speckle.

Space-variant blur occurs when imaging through volume turbulence over sufficiently large fields of view. Space-variant effects are particularly severe in horizontal-path imaging, slant-path (air-to-ground or ground-to-air) geometries, and ground-based imaging of low-elevation satellites or astronomical objects. In these geometries, the isoplanatic angle can be comparable to or even smaller than the diffraction-limited resolution angle. We report on a postdetection correction method that seeks to correct for the effects of space-variant aberrations, with the goal of reconstructing near-diffraction-limited imagery. Our approach has been to generalize the method of phase-diverse speckle (PDS) by using a physically motivated distributed-phase-screen model. Simulation results are presented that demonstrate the reconstruction of near-diffraction-limited imagery under both matched and mismatched model assumptions. In addition, we present evidence that PDS could be used as a beaconless wavefront sensor in a multiconjugate adaptive optics system when imaging extended scenes.