Name
Abstract | ||
|---|---|---|
Template matching is a very topical issue in a wide range of imaging applications. Mathematical morphology offers the hit-or-miss transform, an operator which has been successfully applied for template matching in binary images. More recently, it has been extended to grayscale images and even to multivariate images. Nevertheless, these extensions, despite being relevant from a theoretical point-of-view, might lack practical interest due to the inherent difficulty to set up correctly the transform and its parameters (e.g. the structuring functions). In this paper, we propose a new and more intuitive operator which allows for morphological template matching in multivariate images from both a spatial and spectral point of view. We illustrate the potential of this operator in the context of remote sensing. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.imavis.2012.07.002 | Image Vision Comput. |
Keywords | Field | DocType |
spectral morphological template matching,inherent difficulty,template matching,binary image,spectral point,imaging application,multivariate image,morphological template,practical interest,mathematical morphology,intuitive operator,remote sensing | Template matching,Computer vision,Pattern recognition,Computer science,Mathematical morphology,Multivariate statistics,Binary image,Operator (computer programming),Artificial intelligence,Hit-or-miss transform,Structuring,Grayscale | Journal |
Volume | Issue | ISSN |
30 | 12 | 0262-8856 |
Citations | PageRank | References |
10 | 0.57 | 9 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jonathan Weber | 1 | 39 | 4.59 |
| Sébastien Lefèvre | 2 | 303 | 46.92 |