Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Modeling and real-time estimation of signal-dependent noise in quantum-limited imaging
ISPRA'07 Proceedings of the 6th WSEAS International Conference on Signal Processing, Robotics and Automation
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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.