1966
DOI: 10.1002/j.1538-7305.1966.tb01052.x
|View full text |Cite
|
Sign up to set email alerts
|

Predictive Quantizing Systems (Differential Pulse Code Modulation) for the Transmission of Television Signals

Abstract: Differential pulse code modulation (DP CM) and predictive quantizing are two names for a technique used to encode analog signals into digital pulses suitable for transmission over binary channels. It is the purpose of this paper to determine what kind of performance can be expected from well‐designed systems of this type when used to encode television signals. Systems using both previous sample and previous line feedback are considered. A procedure is presented for the design of nonadaptive, time invariant sys… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
20
0
1

Year Published

1966
1966
1999
1999

Publication Types

Select...
6
3
1

Relationship

0
10

Authors

Journals

citations
Cited by 180 publications
(21 citation statements)
references
References 5 publications
0
20
0
1
Order By: Relevance
“…The mos t prevelant metho d of spatial cod i ng is to predict the next picture value from past values and quantize only the "error " si gnal , which is defined as the difference between the actua l and predicted values [ 8,34].…”
Section: Predictive Methodsmentioning
confidence: 99%
“…The mos t prevelant metho d of spatial cod i ng is to predict the next picture value from past values and quantize only the "error " si gnal , which is defined as the difference between the actua l and predicted values [ 8,34].…”
Section: Predictive Methodsmentioning
confidence: 99%
“…An important example of linear predictive co ding is differential pulse code modulation (DPCM) which is based on the notion of quantizing a prediction error signal [3,4,6,7]. Note, in Figure 1, the predictions are based on previously quantized gray-levels and not on the original unquantized gray-levels.…”
Section: Differential Pulse Code Modulationmentioning
confidence: 99%
“…Studies of image autocorrelation data have been performed for several types of images in conjunction with the development of methods for image data compression (Kretzmer, 1952;O'Neal, 1966;Huang, 1965). These studies indicate that this is indeed an excellent model for a wide variety of scanned pictorial data (Franks, 1966;Habibi and Wintz, 1971).…”
Section: Scene Autocorrelation Modelmentioning
confidence: 99%