Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
1981 | 10.1109/TPAMI.1981.4767100 | IEEE Trans. Pattern Anal. Mach. Intell. |
Keywords | Field | DocType |
measurement system,noise,signal processing,differential operators,transfer functions,layout,image restoration,wiener filter,digital image processing,deconvolution,degradation | Signal processing,Computer vision,Physical quantity,Computer science,Measured quantity,Differential operator,Transfer function,Artificial intelligence,Image restoration,Digital image processing,Computation | Journal |
Volume | Issue | ISSN |
3 | 3 | 0162-8828 |
Citations | PageRank | References |
1 | 0.39 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| John S. Ostrem | 1 | 34 | 15.79 |
| David G. Falconer | 2 | 9 | 1.84 |