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

被引:12
|
作者
Kwan, Chiman [1 ]
Larkin, Jude [1 ]
Budavari, Bence [1 ]
Chou, Bryan [1 ]
Shang, Eric [2 ]
Tran, Trac D. [3 ]
机构
[1] Appl Res LLC, Rockville, MD 20850 USA
[2] Leidos, Columbia, MD 21046 USA
[3] Johns Hopkins Univ, Dept Elect & Comp Engn, Baltimore, MD 21218 USA
关键词
perceptually lossless compression; error recovery; maritime and sonar images; JPEG2000; X264; X265; Daala;
D O I
10.3390/computers8020032
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页数:21
相关论文
共 50 条
  • [1] Codec for transfer Maritime Images in Bandwidth Constrained
    Fahmi, Shakeeb S.
    Krylov, Yuriy E.
    Hasan, Y. A. A.
    Kostikova, Elena, V
    MARINE INTELLECTUAL TECHNOLOGIES, 2020, (03): : 164 - 171
  • [2] COMPRESSION CODECS FOR CONTRIBUTION APPLICATIONS
    BAREZZANI, M
    BURZI, G
    SPERANDIO, L
    ELECTRICAL COMMUNICATION, 1993, (03): : 220 - 226
  • [3] Sonar feature-based bandwidth compression
    Saghri, John A.
    Tescher, Andrew G.
    Journal of Visual Communication and Image Representation, 1993, 4 (02)
  • [4] Tiny Generative Image Compression for Bandwidth-Constrained Sensor Applications
    Koerber, Nikolai
    Siebert, Andreas
    Hauke, Sascha
    Mueller-Gritschneder, Daniel
    20TH IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA 2021), 2021, : 564 - 569
  • [5] A comparative analysis of dynamic range compression techniques in IR images for maritime applications
    Rossi, Alessandro
    Acito, Nicola
    Diani, Marco
    Luison, Cristian
    Olivieri, Monica
    Barani, Gianni
    AIRBORNE INTELLIGENCE, SURVEILLANCE, RECONNAISSANCE (ISR) SYSTEMS AND APPLICATIONS X, 2013, 8713
  • [6] Bandwidth constrained cooperative object detection in images
    Marez, Diego
    Nans, Lena
    Borden, Samuel
    ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN DEFENSE APPLICATIONS IV, 2022, 12276
  • [7] Comparison of effects of sonar bandwidth for underwater target classification
    Azimi-Sadjadi, MR
    Yao, D
    Li, DH
    Jamshidi, AA
    Dobeck, GJ
    DETECTION AND REMEDIATION TECHNOLOGIES FOR MINES AND MINELIKE TARGETS V, PTS 1 AND 2, 2000, 4038 : 300 - 310
  • [8] Comparison of Modern Compression Standards on Medical Images for Telehealth Applications
    Wang, Y.
    Tohidypour, H. R.
    Pourazad, M. T.
    Nasiopoulo, P.
    Leung, V. C. M.
    2023 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS, ICCE, 2023,
  • [9] BANDWIDTH COMPRESSION OF IMAGES - USING TRANSFORM TECHNIQUES
    SOAME, TA
    GEC-JOURNAL OF SCIENCE & TECHNOLOGY, 1982, 48 (01): : 17 - 23
  • [10] BANDWIDTH COMPRESSION OF HIGH QUALITY IMAGES.
    Troxel, D.E.
    Schreiber, W.F.
    Grass, R.
    Hoover, G.
    Sharpe, R.
    Conference Record - International Conference on Communications, 1980, 2 : 1 - 31