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Proceedings Paper

Compressed imagery detection rate through map seeking circuit (MSC) pattern recognition
Author(s): Kathy A. Newtson; Charles C. Creusere
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Paper Abstract

This research investigates the features retained after image compression for automatic pattern recognition purposes. Images were significantly compressed using open-source JPEG and JPEG2000 compression algorithms. The original and compressed images were processed with a Map Seeking Circuit (MSC) pattern recognition algorithm. [1] The resulting target detection rates for the compressed images were very similar to the original images, which included compression rates ranging from 10 to 0.2. Target detection location precision and target aspect were degraded for the lowest compression rates.

Paper Details

Date Published: 19 May 2016
PDF: 11 pages
Proc. SPIE 9874, Remotely Sensed Data Compression, Communications, and Processing XII, 98740E (19 May 2016); doi: 10.1117/12.2224120
Show Author Affiliations
Kathy A. Newtson, Johns Hopkins Univ. Applied Physics Lab., LLC (United States)
Charles C. Creusere, New Mexico State Univ. (United States)

Published in SPIE Proceedings Vol. 9874:
Remotely Sensed Data Compression, Communications, and Processing XII
Bormin Huang; Chein-I Chang; Chulhee Lee, Editor(s)

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