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Norman S. Kopeika

Researcher at Ben-Gurion University of the Negev

Publications -  371
Citations -  5452

Norman S. Kopeika is an academic researcher from Ben-Gurion University of the Negev. The author has contributed to research in topics: Image restoration & Optical transfer function. The author has an hindex of 36, co-authored 371 publications receiving 5221 citations. Previous affiliations of Norman S. Kopeika include Ariel University & University of Pennsylvania.

Papers
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Proceedings ArticleDOI

Restoration of satellite images based on atmospheric MTF

TL;DR: In this paper, the atmospheric Wiener filter was used to correct for turbulence and aerosol blur and path radiance simultaneously in digital restoration of AVHRR imagery over the five wavelength bands of the satellite instrumentation.
Journal ArticleDOI

Myopic Deconvolution of Adaptive Optics Images by use of Object and Point-Spread Function Power Spectra: Comment.

TL;DR: It is suggested here that the lack of total image correction that is typical in adaptive optics (AO) imaging can be attributed in part to blur derived from small-angle scatter of light by aerosols, as it is a well-established fact that such atmospheric blur is dominant in satellite imagery.
Proceedings ArticleDOI

Effects of aerosol forward scatter on atmospheric coherence diameter: theory and validation

TL;DR: In this article, a correction to the definition of the atmospheric coherence diameter is suggested, based on the existence of an aerosol MTF which is often the dominant ingredient of atmospheric MTF.
Proceedings ArticleDOI

Contrast vs noise effects on image quality

TL;DR: This research attempts to construct a reliable quantitative means of characterizing the perceptual difference between target and background by evaluating the extent to which it is possible to discriminate an object which has merged with its surroundings, in noise-limited and contrast limited images.
Proceedings ArticleDOI

Vibrated image restoration from two consecutive images

TL;DR: A vibration motion estimation method from a minimal sequence of two images is presented, carried out in the frequency domain using a new analytical motion OTF calculation method.