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Proceedings Paper

Dynamic range compression deconvolution using A-law and μ-law algorithms
Author(s): Bahareh Haji-saeed; Sandip K. Sengupta; William D. Goodhue; Jed Khoury; Charles L. Woods; John Kierstead
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Paper Abstract

In this paper the A-law/μ-law Dynamic Range Compression algorithm used in telecommunication systems is proposed for the first time for nonlinear Dynamic Range Compression image deconvolution. In the proposed setup, a joint image of the blurred input information and the blur impulse response are jointly Fourier-transformed via a lens to a CCD camera which acts as a square-law receiver. The CCD camera is responsible for mixing the Fourier transforms of the impulse response and the distorted image to compensate for the phase distortion and then the A-law/μ-law nonlinear transformation is responsible for enhancing both the high frequencies and the signal-to-noise ratio. The proposed technique is supported by computer simulation.

Paper Details

Date Published: 9 April 2007
PDF: 7 pages
Proc. SPIE 6574, Optical Pattern Recognition XVIII, 65740D (9 April 2007); doi: 10.1117/12.719585
Show Author Affiliations
Bahareh Haji-saeed, Univ. of Massachusetts, Lowell (United States)
Solid State Scientific Corp. (United States)
Sandip K. Sengupta, Univ. of Massachusetts, Lowell (United States)
William D. Goodhue, Univ. of Massachusetts, Lowell (United States)
Jed Khoury, Air Force Research Lab. (United States)
Charles L. Woods, Air Force Research Lab. (United States)
John Kierstead, Solid State Scientific Corp. (United States)


Published in SPIE Proceedings Vol. 6574:
Optical Pattern Recognition XVIII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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