Video Enhancement for Underwater Exploration Using Forward Looking Sonar

  • Kio Kim
  • Nicola Neretti
  • Nathan Intrator
Conference paper

DOI: 10.1007/11864349_51

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4179)
Cite this paper as:
Kim K., Neretti N., Intrator N. (2006) Video Enhancement for Underwater Exploration Using Forward Looking Sonar. In: Blanc-Talon J., Philips W., Popescu D., Scheunders P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2006. Lecture Notes in Computer Science, vol 4179. Springer, Berlin, Heidelberg

Abstract

The advances in robotics and imaging technologies have brought various imaging devices to the field of the unmanned exploration of new environments. Forward looking sonar is one of the newly emerging imaging methods employed in the exploration of underwater environments. While the video sequences produced by forward looking sonar systems are characterized by low signal-to-noise ratio, low resolution and limited range of sight, it is expected that video enhancement techniques will facilitate the interpretation of the video sequences. Since the video enhancement techniques for forward looking sonar video sequences are applicable to most of the forward looking sonar sequences, the development of such techniques is more crucial than developing techniques for optical camera video enhancement, where only specially produced video sequences can benefit the techniques. In this paper, we introduce a procedure to enhance forward looking sonar video sequences via incorporating the knowledge of the target object obtained in previously observed frames. The proposed procedure includes inter-frame registration, linearization of image intensity, and maximum a posteriori fusion of images in the video sequence. The performance of this procedure is verified by enhancing video sequences of Dual-frequency Identification Sonar (DIDSON), the market leading forward looking sonar system.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Kio Kim
    • 1
  • Nicola Neretti
    • 1
  • Nathan Intrator
    • 1
  1. 1.Institute for Brain and Neural SystemsBrown UniversityProvidenceUSA

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