Noise-parameter modeling and estimation for x-ray fluoroscopy

Tommaso Cerciello, Mario Cesarelli, Luigi Paura, Paolo Bifulco, Maria Romano, Robert Allen

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In fluoroscopy quantum noise is dominant with respect to other common noise sources, whose effects can be often neglected. Quantum noise is originated by the limited number of photons (low-dose X-ray) involved in fluoroscopic image formation; this noise is commonly modeled as Poisson distributed. Estimation of noise-parameters is required for evaluation of X-ray digital imaging sensors and in several image processing applications (e.g. denoising). The first aim of this work is to validate the analytically derived noise-parameter models by real fluoroscopic image sequences, also considering non-linear gray level mappings currently employed by fluoroscopic devices. A plain procedure for estimation of noise pixel-intensity variance as a function of mean pixel-intensity, which does not require specific test-objects but only some images screening a still scene, has been provided. Besides, a procedure for noise-parameter estimation by differencing fluoroscopic static images has been proposed. It computes image-pair differences, estimates concise parameters of the resulting Skellam distribution and, then, quotes Poisson noise-parameters. Image sequences of a simple step-phantom, acquired with a conventional fluoroscopic device, were utilized for performing the noise measurements. Experimental results confirmed a great agreement of the measured noise-parameters with those analytically derived and the possibility to use static images to estimate noise.

Original languageEnglish
Title of host publicationACM International Conference Proceeding Series
Publication statusPublished - 2011
Event4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11 - Barcelona, Spain
Duration: Oct 26 2011Oct 29 2011


Other4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11


  • fluoroscopic images
  • noise estimation
  • quantum noise
  • Skellam distribution
  • white compression

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software


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