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Open AccessArticle

A Comparison of Compression Codecs for Maritime and Sonar Images in Bandwidth Constrained Applications

1
Applied Research, LLC, Rockville, MD 20850, USA
2
Leidos, Columbia, MD 21046, USA
3
Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
*
Author to whom correspondence should be addressed.
Computers 2019, 8(2), 32; https://doi.org/10.3390/computers8020032
Received: 14 February 2019 / Revised: 20 April 2019 / Accepted: 24 April 2019 / Published: 28 April 2019
(This article belongs to the Special Issue Vision, Image and Signal Processing (ICVISP))
Since lossless compression can only achieve two to four times data compression, it may not be efficient to deploy lossless compression in bandwidth constrained applications. Instead, it would be more economical to adopt perceptually lossless compression, which can attain ten times or more compression without loss of important information. Consequently, one can transmit more images over bandwidth limited channels. In this research, we first aimed to compare and select the best compression algorithm in the literature to achieve a compression ratio of 0.1 and 40 dBs or more in terms of a performance metric known as human visual system model (HVSm) for maritime and sonar images. Our second objective was to demonstrate error concealment algorithms that can handle corrupted pixels due to transmission errors in interference-prone communication channels. Using four state-of-the-art codecs, we demonstrated that perceptually lossless compression can be achieved for realistic maritime and sonar images. At the same time, we also selected the best codec for this purpose using four performance metrics. Finally, error concealment was demonstrated to be useful in recovering lost pixels due to transmission errors. View Full-Text
Keywords: perceptually lossless compression; error recovery; maritime and sonar images; JPEG2000; X264; X265; Daala perceptually lossless compression; error recovery; maritime and sonar images; JPEG2000; X264; X265; Daala
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Kwan, C.; Larkin, J.; Budavari, B.; Chou, B.; Shang, E.; Tran, T.D. A Comparison of Compression Codecs for Maritime and Sonar Images in Bandwidth Constrained Applications. Computers 2019, 8, 32.

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