Performance evaluation of the fractional wavelet filter: A low-memory image wavelet transform for multimedia sensor networks

Stephan Rein, Martin Reisslein

Research output: Contribution to journalArticle

29 Scopus citations

Abstract

Existing image wavelet transform techniques exceed the computational and memory resources of low-complexity wireless sensor nodes. In order to enable multimedia wireless sensors to use image wavelet transforms techniques to pre-process collected image sensor data, we introduce the fractional wavelet filter. The fractional wavelet filter computes the wavelet transform of a 256 × 256 grayscale image using only 16-bit fixed-point arithmetic on a micro-controller with less than 1.5 kbyte of RAM. We comprehensively evaluate the resource requirements (RAM, computational complexity, computing time) as well as image quality of the fractional wavelet filter. We find that the fractional wavelet transform computed with fixed-point arithmetic gives typically negligible degradations in image quality. We also find that combining the fractional wavelet filter with a customized wavelet-based image coding system achieves image compression competitive to the JPEG2000 standard.

Original languageEnglish (US)
Pages (from-to)482-496
Number of pages15
JournalAd Hoc Networks
Volume9
Issue number4
DOIs
StatePublished - Jun 1 2011

Keywords

  • Image sensor
  • Image transform
  • In-network processing
  • Integer (fixed-point) arithmetic
  • Lifting computations
  • Wavelet transform
  • Wireless sensor network

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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