Name
Abstract | ||
|---|---|---|
An iterative filter for locally estimating the center of the clusters present in multi-spectral images is developed. In each iteration and for each pixel, an energy function computed for windows of increasing size is evaluated. The initial window size is defined as a function of the separability between neighboring pixels. The increments of the window size axe a function of the internal to external entropy ratio of discs of consecutive radii. For a,given pixel, the minimum value of the energy function is preserved and used as the initial guess for the next iteration. This minimum corresponds to the estimated point in which a state of higher order emerges. The scheme proposed was tested on a set of synthetical images, and compared to the output of the iterative median filter and to the k-Means algorithm, showing better performance than these ones. Results axe shown on dermatological and fundus digital images. |
Year | Venue | Keywords |
|---|---|---|
2002 | PROCEEDINGS OF THE 6TH JOINT CONFERENCE ON INFORMATION SCIENCES | mean shift |
Field | DocType | Citations |
Algorithm,Mean-shift,Mathematics | Conference | 0 |
PageRank | References | Authors |
0.34 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gabriela Maletti | 1 | 2 | 1.54 |
| Bjarne Ersbøll | 2 | 450 | 38.06 |
| Knut Conradsen | 3 | 311 | 32.35 |