1 July 2009 Image deblurring through static or time-varying random perturbation medium
Author Affiliations +
Abstract
In a large plurality of applications, imaging quality is significantly reduced due to existence of static or time-varying random perturbation media. An example of such a medium can be a diffusive window through which we wish to image an object located behind, and not in proximity to, the window. Another example can be localized flow of turbulence (above hot surfaces such as black roads) or of aerosols distorting the imaging resolution of objects positioned behind the perturbation. We present a new deblurring approach for obtaining highly resolved imaging of objects positioned behind static or time-varying random perturbation media. The proposed approach for extraction of the high spatial frequencies is based on iterative computation similar to the well-known Gerchberg-Saxton algorithm for phase retrieval. By focusing our camera onto three planes positioned between the imaging camera and the perturbation, we are able to retrieve the phase distribution of those planes and then reconstruct the intensity of the object by numerical free space propagation of this extracted complex field to the estimated position of the object.
©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)
Eran Gur and Zeev Zalevsky "Image deblurring through static or time-varying random perturbation medium," Journal of Electronic Imaging 18(3), 033016 (1 July 2009). https://doi.org/10.1117/1.3224953
Published: 1 July 2009
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CITATIONS
Cited by 13 scholarly publications.
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KEYWORDS
Diffusers

Reconstruction algorithms

Cameras

Image resolution

Image sensors

Optical sensors

Turbulence

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