CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 1981 vol.3 Issue No.03 - March
Issue No.03 - March (1981 vol.3)
John S. Ostrem , MEMBER, IEEE, Bioengineering Research Center, SRI International, Menlo Park, CA 94025.
David G. Falconer , MEMBER, IEEE, Artificial Intelligence Center, SRI International, Menlo Park, CA 94025; Remote Measurements Laboratory, SRI International, Menlo Park, CA 94025.
A technique is described for restoring signals, images, and other physical quantities that have been distorted or degraded by an imperfect measurement system. This technique is based upon the application of a specific differential operator to the measured quantity. For digital implementation, its advantages compared to other restoration techniques are simplicity, computational efficiency, and reduced core memory requirements. Calculations for a one-dimensional example indicate that restorations comparable in quality to Wiener-filter restorations are obtained with better than an order of magnitude decrease in computation time.
John S. Ostrem, David G. Falconer, "A Differential Operator Technique for Restoring Degraded Signals and Images", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.3, no. 3, pp. 278-284, March 1981, doi:10.1109/TPAMI.1981.4767100