Compressed imagery detection rate through map seeking circuit (MSC) pattern recognition

Kathy A. Newtson; Charles C. Creusere

doi:10.1117/12.2224120

19 May 2016 Compressed imagery detection rate through map seeking circuit (MSC) pattern recognition

Kathy A. Newtson, Charles C. Creusere

Proceedings Volume 9874, Remotely Sensed Data Compression, Communications, and Processing XII; 98740E (2016) https://doi.org/10.1117/12.2224120
Event: SPIE Commercial + Scientific Sensing and Imaging, 2016, Baltimore, MD, United States

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.

Citation Download Citation

Kathy A. Newtson and Charles C. Creusere "Compressed imagery detection rate through map seeking circuit (MSC) pattern recognition", Proc. SPIE 9874, Remotely Sensed Data Compression, Communications, and Processing XII, 98740E (19 May 2016); https://doi.org/10.1117/12.2224120

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