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Dictionary Approaches to Image Compression and ReconstructionThis paper proposes using a collection of parameterized waveforms, known as a dictionary, for the purpose of medical image compression. These waveforms, denoted as phi(sub gamma), are discrete time signals, where gamma represents the dictionary index. A dictionary with a collection of these waveforms is typically complete or overcomplete. Given such a dictionary, the goal is to obtain a representation image based on the dictionary. We examine the effectiveness of applying Basis Pursuit (BP), Best Orthogonal Basis (BOB), Matching Pursuits (MP), and the Method of Frames (MOF) methods for the compression of digitized radiological images with a wavelet-packet dictionary. The performance of these algorithms is studied for medical images with and without additive noise.
Document ID
Document Type
Reprint (Version printed in journal)
Ziyad, Nigel A. (NASA Goddard Space Flight Center Greenbelt, MD United States)
Gilmore, Erwin T. (Howard Univ. Washington, DC United States)
Chouikha, Mohamed F. (Howard Univ. Washington, DC United States)
Date Acquired
August 19, 2013
Publication Date
January 1, 1998
Subject Category
Computer Programming and Software
Meeting Information
Signal and Image Processing(Las Vegas, NV)
Distribution Limits
Work of the US Gov. Public Use Permitted.
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