Compressive Underwater Video Camera

Abstract

The primary long-term goal of our research team is the development of image compression transforms with high compression ratios (consistently exceeding 200:1) that can facilitate the transmission of moderate resolution imagery (e.g., S-VHS format) across low-bandwidth channels such as acoustic uplinks from autonomous underwater vehicles (AUVs). Secondary goals include the development of image quality measures (IQMs) that can support rigorous comparison between compression transforms, as well as the implementation of best-performance transforms on fast digital signal processors (DSPs) or reconfigurable architectures suitable for AUVs. A tertiary goal, which we plan to explore in depth in future research, is the integration of image compression with automated target recognition (ATR). Two cases are of interest to this study. First, we have shown that one can achieve increased processing efficiency by applying specially configured ATR operations to compressed imagery. Second, we have developed techniques for prefiltering multi-target imagery to downselect candidate targets prior to compression. The first technique uses compression to increase computational efficiency of ATR processes, while the second technique employs ATR to increase the effective compression ratio. In FY98, our primary goal was to establish that the compression transform developed under the scope of this study, called EBLAST (Enhanced Blurring, Local Averaging, Sharpening, and Thresholding), performed better than published compression transforms such as EPIC, SPIHT, VPIC, and wavelet packet compression. The second goal was to implement EBLAST, or its predecessor BLAST, on DSP-based hardware, to determine feasibility for underwater image compression via laboratory or field tests. A third objective emphasized the enhancement of our existing suite of IQMs to include measures of linear feature distortion, as well as statistical techniques for quantifying the blurring effect of a compression transform.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1998
Accession Number
ADA551193

Entities

People

  • Frank M. Caimi
  • Gerhard X. Ritter
  • Mark S. Schmalz

Organizations

  • Harbor Branch Oceanographic Institute

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Automated Target Recognition
  • Autonomous Underwater Vehicles
  • Autonomous Vehicles
  • Cameras
  • Communication Channels
  • Compression
  • Compression Ratio
  • Data Compression
  • Engineering
  • Frequency
  • Image Compression
  • Image Processing
  • Image Reconstruction
  • Target Recognition
  • Video
  • Video Cameras

Readers

  • Image Processing and Computer Vision.
  • Software Engineering