Fractional order color image processing
| dc.contributor.author | Henriques, Manuel | |
| dc.contributor.author | Valério, Duarte | |
| dc.contributor.author | Gordo, Paulo | |
| dc.contributor.author | Melício, Rui | |
| dc.date.accessioned | 2022-01-11T11:03:59Z | |
| dc.date.available | 2022-01-11T11:03:59Z | |
| dc.date.issued | 2021-02 | |
| dc.description.abstract | Many image processing algorithms make use of derivatives. In such cases, fractional derivatives allow an extra degree of freedom, which can be used to obtain better results in applications such as edge detection. Published literature concentrates on grey-scale images; in this paper, algorithms of six fractional detectors for colour images are implemented, and their performance is illustrated. The algorithms are: Canny, Sobel, Roberts, Laplacian of Gaussian, CRONE, and fractional derivative. | por |
| dc.identifier.authoremail | nd | |
| dc.identifier.authoremail | nd | |
| dc.identifier.authoremail | nd | |
| dc.identifier.authoremail | ruimelicio@gmail.com | |
| dc.identifier.doi | 10.3390/math9050457 | por |
| dc.identifier.scientificarea | 246 | por |
| dc.identifier.uri | http://hdl.handle.net/10174/30734 | |
| dc.language.iso | eng | por |
| dc.peerreviewed | yes | por |
| dc.rights | openAccess | por |
| dc.subject | Fractional Derivatives | por |
| dc.subject | Image Processing | por |
| dc.subject | Colour Images | por |
| dc.subject | Satellite Images | por |
| dc.subject | Very-High- Resolution Satellite | por |
| dc.subject | Satellite Imagery Processing | por |
| dc.title | Fractional order color image processing | por |
| dc.type | article |