Noise enhanced imaging
Abstract
Objects with low intensities are below detection levels. A class of noise-induced cooperative phenomena, called Stochastic Resonance (SR) has been shown to enhance and sustain the dynamic response of a nonlinear system to input stimuli in numerous studies. In SR, an optimum, nonzero value of noise maximizes the counter-intuitive cooperation between noise and the input signal. However, a non-optimal value, will not maximize the output but either minimize it or annihilate it completely.
Most imaging systems function by decreasing or eliminating noise from the input. In this paper, we demonstrate a method that allows the imaging of objects with sub-threshold intensities, using additive noise. Additive noise is used to drive the intensity ofthe test object so that it is detected by a threshold detector. We also demonstrate that performing the simulation with a sufficiently large number of trials, decreases the optimum value of noise required for a good image quality.
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