ust intersect video pulses that form textual characters, in the scanned image, at a point that occurs above a pre-defined noise amplitude but below the peak amplitudes of these pulses. One technique for sensing the proper noise amplitude is to observe the occurrence of single isolated pixels that occur throughout the scanned image. Specifically, in the KIMS system, a microfilm image is scanned at a typical density of 200 pixels to the inch (approximately 79 pixel/cm). Noise generally takes the form of an isolated pixel of one color, i.e. black, surrounded by pixels of another color, i.e. white. A pixel of this size is simply not readily visible to an average reader. As such, a single isolated pixel does not form any part of a textual character but is instead noise. Single pixel noise can be one-dimensionally isolated wherein a single pixel is "on" while its neighbors to its left and right are both "off", or two-dimensionally isolated wherein the single pixel is "on" while its neighbors to the left, right, above and below and possibly also those which are diagonally oriented to the single pixel are all "off".
Ideally, then, one could set the threshold level to an appropriate level to filter out single pixel noise from the six bit digitized video. Unfortunately, in practice, single pixel noise can occur at various intensity levels throughout the full range of video amplitude in the scanned image thereby significantly complicating the process of thresholding. Specifically, first, single pixel noise can occur on the peaks of the video signal which correspond to detected pixels that form a textual character that appears on a background having the highest contrast, e.g. those pixels that form a black character on a white background. If the threshold were to be set to this level, then disadvantageously any character that is situated on a background having a reduced contrast, e.g. a gray character on a white background, would be entirely removed from the image. Specifically, the pixels which form these characters would n