Name
Abstract | ||
|---|---|---|
This paper deals with moment invariants with respect to image blurring. It is mainly a reaction to the works of Zhang and Chen , recently published in these Transactions. We present a general method on how to construct blur invariants from arbitrary moments and show that it is no longer necessary to separately derive the invariants for each polynomial basis. We show how to discard dependent terms in blur invariants definition and discuss a proper implementation of the invariants in orthogonal bases using recurrent relations. An example for Legendre moments is given. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TIP.2011.2159235 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
blur invariants,blur invariants definition,orthogonal base,dependent term,general method,arbitrary moments,polynomial basis,legendre moment,moment invariants,arbitrary moment,paper deal,image restoration,image moments,method of moments,image recognition,polynomials,image registration,legendre polynomials,correlation | Polynomial basis,Polynomial,Mathematical analysis,Legendre polynomials,Artificial intelligence,Image restoration,Image moment,Method of moments (statistics),Pattern recognition,Pure mathematics,Invariant (mathematics),Image registration,Mathematics | Journal |
Volume | Issue | ISSN |
20 | 12 | 1941-0042 |
Citations | PageRank | References |
7 | 0.46 | 14 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jaroslav Kautsky | 1 | 108 | 20.75 |
| Jan Flusser | 2 | 3067 | 215.61 |