Lens-motor noise suppression for digital cameras

In this paper, we formulate a speech enhancement problem under multiple hypotheses, assuming an indicator for the lens motor noise presence is available in the time domain. This approach is largely based on an existing speech enhancement algorithm, and was adapted to specifically handle lens motor noises. Hypothetical presence of speech together with an estimation of the stationary noise and the lens motor noise, are considered in the calculation of the desired signal spectral coefficients. Cost parameters control the trade-off between speech distortion and residual transient noise. An optimal estimator, which minimizes the mean-square error of the log-spectral amplitude, is derived, while taking into account the probability of erroneous detection. Experimental results demonstrate a substantial suppression of the motor noise with a minimal degrade to the perceived quality of the desired signal.