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Journal of Object Technology
Article . 2005 . Peer-reviewed
Data sources: Crossref
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DBLP
Article . 2021
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Synthetic Image Sequence Compression.

Authors: Lyon, Douglas A.;

Synthetic Image Sequence Compression.

Abstract

This paper describes a technique for compressing computer screen shots into a GIF animation file. The goal is to distribute the animations, to a variety of browsers, without requiring a plug-in or helper application. We seek to minimize the size of the image sequence, while maximizing the signal to noise ratio of the sequence. The GIF animation format has several constraints; images may have a maximum of 256 colors, and the images must all be of the same size. Further, to minimize overhead, we seek to make use of a single color lookup table for the entire animation. Several color quantization algorithms are compared, using SNR (Signal to Noise Ratio) as the metric of quality (as well as subjective appearance). We present the design of an interface, written in Java, and distributed freely using Java Web Start, that employs a well know neural network program and a color quantization algorithm to capture screen shots and save them to the GIF animation. GIF animations represent silent movies, as they have no sound to accompany them. However, they are still in wide use and have applications in entertainment and education. The techniques described are a part of the JSnap project, a joint project between the skunk works of DocJava, Inc. and Fairfield University.

Country
United States
Related Organizations
Keywords

Engineering, Computer Engineering, 620

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold