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An FPGA-Oriented Algorithm for Real-Time Filtering of Poisson Noise in Video Streams, with Application to X-Ray Fluoroscopy

  • G. Castellano
  • D. De Caro
  • D. EspositoEmail author
  • P. Bifulco
  • E. Napoli
  • N. Petra
  • E. Andreozzi
  • M. Cesarelli
  • A. G. M. Strollo
Article
  • 27 Downloads

Abstract

In this paper we propose a new algorithm for real-time filtering of video sequences corrupted by Poisson noise. The algorithm provides effective denoising (in some cases overcoming the filtering performances of state-of-the-art techniques), is ideally suited for hardware implementation, and can be implemented on a small field-programmable gate array using limited hardware resources. The paper describes the proposed algorithm, using X-ray fluoroscopy as a case study. We use IIR filters for time filtering, which largely simplifies hardware cost with respect to previous FIR filter-based implementations. A conditional reset is implemented in the IIR filter, to minimize motion blur, with the help of an adaptive thresholding approach. Spatial filtering performs a conditional mean to further reduce noise and to remove isolated noisy pixels. IIR filter hardware implementation is optimized by using a novel technique, based on Steiglitz–McBride iterative method, to calculate fixed-point filter coefficients with minimal number of nonzero elements. Implementation results using the smallest StratixIV FPGA show that the system uses only, at most, the 22% of the resources of the device, while performing real-time filtering of 1024 × 1024@49fps video stream. For comparison, a previous FIR filter-based implementation, on the same FPGA, in the same conditions and constraints (1024 × 1024@49fps), requires the 80% of the logic resources of the FPGA.

Keywords

Real-time video filtering IIR filtering IIR filter design Poisson noise X-ray videofluoroscopy processing Field-programmable gate array (FPGA) 

Notes

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Electrical Engineering and Information TechnologyUniversity of Napoli Federico IINaplesItaly

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