Improving the visual perception of sonar signals with stochastic resonance
Went, Allison P.
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The goal of this research project is to improve the detection of low-level tonals in LOFARgrams by reducing the negative effects of background noise using stochastic resonance. Stochastic resonance (SR), in general, is a phenomenon whereby the effect of low level signals is enhanced through the addition of noise. It has been invoked as an explanation for a wide range of observations from the periodicity of ice ages to the behavior of crayfish neurons. Recent work has focused on the possibility of applying it to image processing. Both static and moving image improvements have been reported. The basic technique behind the use of stochastic resonance in image processing is to first add a random amount of noise to each pixel in the image. Second, a threshold is applied to the image, so that pixels above the threshold are rounded up to the maximum pixel value, and pixels below the threshold are rounded down to the minimum. The images produced can either be averaged into a single image, or shown in series as a movie. In this thesis, a simulated signal was created and tested to find the amount of noise to add and the threshold to apply in order to maximize the signal-to-noise ratio of an averaged image. It was found that the best result was produced when a threshold was applied without adding any additional noise. This finding shows that the process does not demonstrate stochastic resonance for static images. A theoretical analysis of this result is provided. Although no improvement in the moving images was obvious, an SR effect in the optical nerves cannot be ruled out at this time. A future experiment is recommended that would use human test subjects to determine whether or not SR movies can be used to improve the detectability of low-level signals.
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