Stuart Jefferies

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Removing non-uniform blur and noise from optical images is a very difficult problem to resolve. In this paper we describe a strategy that can be used for solving such problems. We describe how to restore images blurred by an unknown spatially-varying point spread function (PSF) by using a combination of methods including sectioning and phase diversity blind(More)
In this paper, we present an algorithm for the restoration of images with an unknown, spatially-varying blur. Existing computational methods for image restoration require the assumption that the blur is known and/or spatially-invariant. Our algorithm uses a combination of techniques. First, we section the image, and then treat the sections as a sequence of(More)
We use blind deconvolution methods in optical diffusion tomography to reconstruct images of objects imbedded in or located behind turbid media from continuous-wave measurements of the scattered light transmitted through the media. In particular, we use a blind deconvolution imaging algorithm to determine both a deblurred image of the object and the depth of(More)
We show in benchtop experiments that wave-front phase estimation by phase diversity can be significantly improved by simultaneous amplitude estimation. Processing speed, which will be important for real-time wave-front control applications, can be enhanced by use of small-format detectors with pixels that do not fully sample the diffraction limit. Using an(More)
We present a new way to sense atmospheric wave-front phase distortion. Short collimated pulses of laser light at ~350nm are projected from a small auxilliary telescope. Rayleigh scattering from each pulse is recorded over a wide range of height through the main telescope aperture in a continuous sequence of fast video frames by a detector conjugate to(More)
We report a multiframe blind deconvolution algorithm that we have developed for imaging through the atmosphere. The algorithm has been parallelized to a significant degree for execution on high-performance computers, with an emphasis on distributed-memory systems so that it can be hosted on commodity clusters. As a result, image restorations can be obtained(More)
Obtaining high resolution images of space objects from ground based telescopes is challenging, and often requires computational post processing methods to remove blur caused by atmospheric turbulence. In order for an image deblurring (deconvolution) algorithm to be effective, it is important to have a good approximation of the blurring operator. In space(More)
Wave fronts distorted by atmospheric turbulence are well known to demonstrate both spatial and temporal coherence. The duration of the latter depends on the magnitude and distribution of wind velocities in the atmosphere and typically has a value at visible wavelengths close to 10 m for a good observing site. Modern imaging systems are capable of acquiring(More)