Image recovery from data acquired with a charge-coupled-device camera

Abstract

A model for data acquired with the use of a charge-coupled-device camera is given and is then used for developing a new iterative method for restoring intensities of objects observed with such a camera. The model includes the effects of point spread, photoconversion noise, readout noise, nonuniform flat-field response, nonuniform spectral response, and extraneous charge carriers resulting from bias, dark current, and both internal and external background radiation. An iterative algorithm is identified that produces a sequence of estimates converging toward a constrained maximum-likelihood estimate of the intensity distribution of an imaged object. An example is given for restoring images from data acquired with the use of the Hubble Space Telescope.

Strehl-constrained iterative blind deconvolution for post-adaptive-optics data

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Iterative Methods for Image Restoration

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Multiframe sure-let denoising of timelapse fluorescence microscopy images

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