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Proceedings Paper

Image Coders With Semi-Definite And Definite Decoders
Author(s): T. G. Marshall
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Paper Abstract

The special class of convolutional, or nonblock, coding systems which employ both FIR encoders and FIR decoders, or definite decoders, is proposed for real-time processing of sampled data. Fully definite multi-dimensional systems and partially definite, i.e. definite in some dimensions but not in others, are seen to exist. Since such a coding system is necessarily a multi-channel system, for signals of any dimension, some of the properties of multi-channel systems are considered as well as their applications. It is seen that convolutional coders incorporating definite decoders can do several desirable things, normally associated only with block coders, such as noncausal coding; and, in addition, traditional applications of single channel convolutional coders, such as linear prediction and estimation, are also possible in multi-channel systems. Color television image coding is seen to be a natural application for multi-channel coding because of the inherent separation of luminance and chrominance into separate channels. An important property of definite coding systems affecting the economy of 2 and 3 dimensional processing systems, which are used for bandwidth compression, is that the decoder uses only the compressed data, thereby significantly reducing the memory requirements for storage of data corresponding to previous lines and frames. Examples are presented of definite systems which separate color signals into their components, noncausal coders, doders which reduce the visability of noise bursts, and linear predictors with feedback quantizers.

Paper Details

Date Published: 28 December 1979
PDF: 9 pages
Proc. SPIE 0207, Applications of Digital Image Processing III, (28 December 1979); doi: 10.1117/12.958258
Show Author Affiliations
T. G. Marshall, Rutgers University (United States)

Published in SPIE Proceedings Vol. 0207:
Applications of Digital Image Processing III
Andrew G. Tescher, Editor(s)

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