Name
Abstract | ||
|---|---|---|
In this paper, we present an approach for image reconstruction from local phase vectors in the monogenic scale space. The local phase vector contains not only the local phase but also the local orientation of the original signal, which enables the simultaneous estimation of the structural and geometric information. Consequently, the local phase vector preserves a lot of important information of the original signal. Image reconstruction from the local phase vectors can be easily and quickly implemented in the monogenic scale space by a coarse to fine way. Experimental results illustrate that an image can be accurately reconstructed based on the local phase vector. In contrast to the reconstruction from zero crossings, our approach is proved to be stable. Due to the local orientation adaptivity of the local phase vector, the presented approach gives a better result when compared with that of the Gabor phase based reconstruction. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-28649-3_21 | PATTERN RECOGNITION |
Keywords | Field | DocType |
image reconstruction,scale space | Iterative reconstruction,Computer vision,Zero crossing,Phase reconstruction,Computer science,Phasor,Scale space,Gabor filter,Artificial intelligence | Conference |
Volume | ISSN | Citations |
3175 | 0302-9743 | 1 |
PageRank | References | Authors |
0.38 | 5 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Di Zang | 1 | 98 | 12.40 |
| Gerald Sommer | 2 | 269 | 21.93 |