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An enhanced NAS-RIF algorithm for blind image deconvolution

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posted on 2010-01-15, 12:07 authored by Chin Ann Ong, Jonathon Chambers
We enhance the performance of the nonnegativity and support constraints recursive inverse filtering (NAS-RIF) algorithm for blind image deconvolution. The original cost function is modified to overcome the problem of operation on images with different scales for the representation of pixel intensity levels. Algorithm resetting is used to enhance the convergence of the conjugate gradient algorithm. A simple pixel classification approach is used to automate the selection of the support constraint. The performance of the resulting enhanced NAS-RIF algorithm is demonstrated on various images

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Citation

ONG, C.A. and CHAMBERS, J.A., 1999. An enhanced NAS-RIF algorithm for blind image deconvolution. IEEE Transactions on Image Processing, 8(7), pp. 988 - 992

Publisher

© IEEE

Version

  • VoR (Version of Record)

Publication date

1999

Notes

This article was published in the journal IEEE Transactions on Image Processing,[© IEEE] and is also available at: http://ieeexplore.ieee.org/. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

ISSN

1057-7149

Language

  • en

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