Gray-levels can improve the performance of binary image digitizers

The application of gray-scale digitizers to the digitization of binary images of straight-edged silhouettes is considered. A measure of digitization-induced ambiguity is introduced. It is shown that if the gray levels are not quantized and the sampling resolution is sufficiently high, error-free reconstruction of the original binary image from the digitized image is possible. When the total bit-count for the representation of the digitized image is limited, i.e., sampling resolution and quantization accuracy are both finite, error-free reconstruction is usually impossible. The authors´ suggested bit allocation policy is then to increase the quantization accuracy as much as possible, once sufficient sampling resolution has been reached