Name
Abstract | ||
|---|---|---|
A new kind of entropy is proposed, which associates spatial and radiometric properties of images. The possible use of this entropy is shown firstly to measure the effect of picture processing algorithms, then to control the evolution of iterative contextual classification algorithms like Markov random fields |
Year | DOI | Venue |
|---|---|---|
1994 | 10.1109/ICIP.1994.413562 | Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference |
Keywords | Field | DocType |
Markov processes,convergence of numerical methods,entropy,image classification,iterative methods,Markov random fields,contextual classification convergence,iterative contextual classification algorithms,picture processing algorithms,radiometric properties,spatial entropy,spatial properties | Markov process,Maximum-entropy Markov model,Pattern recognition,Computer science,Markov model,Iterative method,Markov chain,Artificial intelligence,Variable-order Markov model,Statistical classification,Contextual image classification | Conference |
Volume | ISBN | Citations |
2 | 0-8186-6952-7 | 2 |
PageRank | References | Authors |
0.65 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Henri Maître | 1 | 485 | 48.90 |
| Isabelle Bloch | 2 | 2123 | 170.75 |
| Marc Sigelle | 3 | 316 | 34.12 |