Low bit-rate compression of underwater imagery based on adaptive hybrid wavelets and directional filter banks

Yang Zhang, Shahriar Negahdaripour, Qingzhong Li

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

A new underwater video compression technique based on adaptive hybrid wavelets and directional filter banks is proposed to achieve both high coding efficiency and good reconstruction quality at very low-bit rates. A key application is the real-time transmission of video through acoustic channels with limited bandwidth, from an autonomous underwater vehicle to a surface station, e.g., for man-in-the-loop monitoring and inspection operations. For intra-frame coding, the method maintains details in texture regions at relatively low bit rates, and overcomes the ringing artifacts within smooth regions. For inter-frame coding, improved efficiency is achieved by making use of: (1) a new spatio-temporal just-noticeable-distortion model to remove perceptual redundancy; (2) motion interpolation to reduce bit rate; and (3) variable-precision in quantizing the residual error. Experiments with underwater video sequences are presented to assess the effectiveness of the proposed approach, in comparison to traditional wavelet-based techniques.

Original languageEnglish (US)
Pages (from-to)96-114
Number of pages19
JournalSignal Processing: Image Communication
Volume47
DOIs
StatePublished - Sep 1 2016

Keywords

  • Directional filter bank
  • Just-noticeable distortion
  • Low bit-rate coding
  • Underwater imagery
  • Video compression
  • Wavelet

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

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