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Journal of Electronic Imaging

Progressive image transmission using a self-supervised back-propagation neural network
Author(s): Wei Gong; K. R. Rao; Michael T. Manry
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Paper Abstract

A new technique for progressive image transmission (PIT) is presented that uses a self-supervised back-propagation neural network discrete cosine transform. The transmission sequence is determined using a back-propagation neural network (BPNN) feature importance function. Simulation results show that the PIT system can be successfully implemented using BPNN. Very good intermediate images are obtained at reasonable bit rates.

Paper Details

Date Published: 1 January 1992
PDF: 7 pages
J. Electron. Imag. 1(1) doi: 10.1117/12.55176
Published in: Journal of Electronic Imaging Volume 1, Issue 1
Show Author Affiliations
Wei Gong, Univ of Texas/Arlington (United States)
K. R. Rao, Univ. of Texas/Arlington (United States)
Michael T. Manry, Univ. of Texas/Arlington (United States)

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