Name
Abstract | ||
|---|---|---|
The vector median filter(VMF) is a useful and common tool for noise removal in color image processing. The drawback of the approach in its gen- eral form is the high computational cost if implemented naively. Indeed it takes O(n m m4s) distance evaluations for computing the filter response, where ms ist the mask size and n m the dimension of the image. In this contribu- tion we propose a general algorithmic optimization framework for reducing the complexity to O(n m m3s ). We discuss the dependency of the VMF on the dis- tance measure and demonstrate that for the square Euclidian distance, the VMF becomes a vector near-mean filter with just O(n m m2s ) distance evaluations. |
Year | Venue | Keywords |
|---|---|---|
2004 | Workshop Farbbildverarbeitung | generic algorithm,median filter |
Field | DocType | Citations |
Computer vision,Median filter,Computer science,Salt-and-pepper noise,Adaptive filter,Kernel adaptive filter,Artificial intelligence,Computation | Conference | 1 |
PageRank | References | Authors |
0.34 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vinh Hong | 1 | 3 | 1.44 |
| Laszlo Csink | 2 | 4 | 1.83 |
| Sahla Bouattour | 3 | 3 | 2.45 |
| Dietrich Paulus | 4 | 377 | 71.34 |