Issue No. 01 - January (1978 vol. 27)
M. Kanefsky , Department of Electrical Engineering, University of Pittsburgh
This paper considers a detection theory approach to the restoration of digitized images. The images are modeled as second-order Markov meshes. This model is not only well suited to a decision approach to smoothing, but it enables computer simulations of images thereby permitting a statistical analysis of restoration techniques. Smoothing procedures that are near optimal in the sense of approaching a nonrealizable bound are demonstrated and evaluated. The achievable reduction in mean-square error is considerable for coarsely quantized pictures. This reduction, for the four-level pictures considered, is somewhat greater than that achievable by linear techniques. The approach actually minimizes the probability of error which may be important for preserving picture features.
image simulations, Decision theory, image enhancement
M. Kanefsky and M. Strintzis, "A Decision Theory Approach to Picture Smoothing," in IEEE Transactions on Computers, vol. 27, no. , pp. 32-36, 1978.