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The joint estimation of an object and the aberrations of an incoherent imaging system from multiple images incorporating phase diversity is investigated. Maximum-likelihood estimation is considered under additive Gaussian and Poisson noise models. Expressions for an aberration-only objective function that accommodates an arbitrary number of diversity images(More)
This paper describes a single-shot spectral imaging approach based on the concept of compressive sensing. The primary features of the system design are two dispersive elements, arranged in opposition and surrounding a binary-valued aperture code. In contrast to thin-film approaches to spectral filtering, this structure results in easily-controllable,(More)
We describe several results characterizing the Hubble Space Telescope from measured point spread functions by using phase-retrieval algorithms. The Cramer-Rao lower bounds show that point spread functions taken well out of focus result in smaller errors when aberrations are estimated and that, for those images, photon noise is not a limiting factor.(More)
The size of infrared camera systems can be reduced by collecting low-resolution images in parallel with multiple narrow-aperture lenses rather than collecting a single high-resolution image with one wide-aperture lens. We describe an infrared imaging system that uses a three-by-three lenslet array with an optical system length of 2.3 mm and achieves(More)
We propose an estimation-theoretic approach to the inference of an incoherent 3D scattering density from 2D scattered speckle field measurements. The object density is derived from the covariance of the speckle field. The inference is performed by a constrained optimization technique inspired by compressive sensing theory. Experimental results demonstrate(More)
y In this paper, a space-alternating generalized expectation-maximization (SAGE) algorithm is presented for the numerical computation of maximum-likelihood (ML) and penalized maximum-likelihood (PML) estimates of the parameters of covariance matrices with linear structure for complex Gaussian processes. By using a less informative hidden-data space and a(More)
Phase-error correction through the optimization of an image-domain sharpness function provides one method for the auto-focus of synthetic aperture radar (SAR) imagery. Several ad-hoc sharpness functions have been proposed, implemented, and analyzed, but none of these has been motivated as the solution to a well-defined statistical estimation problem. In(More)
Deconvolution from wavefront sensing (or self-referenced speckle holography) has previously been proposed as a post-detection processing technique for correcting turbulence-induced wavefront phase-errors in incoherent imaging systems. In this paper, a new methodology is considered for processing the image and wavefront-sensor data in which the method of(More)