Name
Abstract | ||
|---|---|---|
Over the last decade, it has been demonstrated that many systems in science and engineering can be modeled more accurately by fractional-order than integer-order derivatives, and many methods are developed to solve the problem of fractional systems. Due to the extra free parameter order a, fractional-order based methods provide additional degree of freedom in optimization performance. Not surprisingly, many fractional-order based methods have been used in image processing field. Herein recent studies are reviewed in ten sub-fields, which include image enhancement, image denoising, image edge detection, image segmentation, image registration, image recognition, image fusion, image encryption, image compression and image restoration. In sum, it is well proved that as a fundamental mathematic tool, fractional-order derivative shows great success in image processing. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1515/fca-2016-0063 | FRACTIONAL CALCULUS AND APPLIED ANALYSIS |
Keywords | Field | DocType |
fractional-order derivative,fractional calculus,image processing | Template matching,Top-hat transform,Feature detection (computer vision),Binary image,Image processing,Fractional calculus,Image restoration,Digital image processing,Mathematics,Calculus | Journal |
Volume | Issue | ISSN |
19 | 5 | 1311-0454 |
Citations | PageRank | References |
14 | 0.67 | 48 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qi Yang | 1 | 14 | 0.67 |
| Dali Chen | 2 | 60 | 6.10 |
| tiebiao zhao | 3 | 17 | 2.48 |
| Yangquan Chen | 4 | 2257 | 242.16 |