Reduction of obscuration noise using multiple images

Noise that replaces, rather than perturbs, a signal is not amenable to the usual approaches of noise removal. Here, multiple images of a stationary scene are used to reduce random obscuration or dropout noise by the following method. For each image coordinate, a gray-level initial histogram is computed over all the images. The initial histograms are averaged for all image coordinates, and for each image coordinate a gray-level histogram corresponding to the object is derived by subtracting the averaged histogram from the initial one. The gray level of the object is obtained from the resulting object histogram. The effectiveness of this method is confirmed through experiments using a scene obscured by air bubbles in a water tank