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Proceedings Article

Dynamic range compression deconvolution using A-law and μ-law algorithms

[+] Author Affiliations
Bahareh Haji-saeed

Univ. of Massachusetts, Lowell and Solid State Scientific Corp.

Sandip K. Sengupta, William D. Goodhue

Univ. of Massachusetts, Lowell

Jed Khoury, Charles L. Woods

Air Force Research Lab.

John Kierstead

Solid State Scientific Corp.

Proc. SPIE 6574, Optical Pattern Recognition XVIII, 65740D (April 09, 2007); doi:10.1117/12.719585
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From Conference Volume 6574

  • Optical Pattern Recognition XVIII
  • David P. Casasent; Tien-Hsin Chao
  • Orlando, Florida, USA | April 09, 2007

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.

© (2007) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Citation

Bahareh Haji-saeed ; Sandip K. Sengupta ; William D. Goodhue ; Jed Khoury ; Charles L. Woods, et al.
"Dynamic range compression deconvolution using A-law and μ-law algorithms", Proc. SPIE 6574, Optical Pattern Recognition XVIII, 65740D (April 09, 2007); doi:10.1117/12.719585; http://dx.doi.org/10.1117/12.719585


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