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  • Research Article
  • Open Access

Cost-Effective Video Filtering Solution for Real-Time Vision Systems

EURASIP Journal on Advances in Signal Processing20052005:568069

  • Received: 23 December 2003
  • Published:


This paper presents an efficient video filtering scheme and its implementation in a field-programmable logic device (FPLD). Since the proposed nonlinear, spatiotemporal filtering scheme is based on order statistics, its efficient implementation benefits from a bit-serial realization. The utilization of both the spatial and temporal correlation characteristics of the processed video significantly increases the computational demands on this solution, and thus, implementation becomes a significant challenge. Simulation studies reported in this paper indicate that the proposed pipelined bit-serial FPLD filtering solution can achieve speeds of up to 97.6 Mpixels/s and consumes 1700 to 2700 logic cells for the speed-optimized and area-optimized versions, respectively. Thus, the filter area represents only 6.6 to 10.5% of the Altera STRATIX EP1S25 device available on the Altera Stratix DSP evaluation board, which has been used to implement a prototype of the entire real-time vision system. As such, the proposed adaptive video filtering scheme is both practical and attractive for real-time machine vision and surveillance systems as well as conventional video and multimedia applications.

Keywords and phrases

  • VHDL implementation
  • FPLD
  • bit-serial approach
  • pipelined solution
  • video filtering and enhancement
  • nonlinear adaptive filter design

Authors’ Affiliations

Laboratoire Traitement du Signal et Instrumentation, Unité Mixte de Recherche CNRS 5516, Université Jean Monnet, 10 rue Barrouin, Saint-Etienne, 42000, France
Multimedia Laboratory, The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, ON, M5S 3G4, Canada


© Viktor Fischer et al. 2005

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.