Blur recognition using second fundamental form of image surface
Fragment książki (Materiały konferencyjne)
MNiSW
15
WOS
| Status: | |
| Autorzy: | Kvyetnyy Roman N., Bunyak Yuriy, Sofina Olga, Kotyra Andrzej, Romaniuk Ryszard S., Tuleshova Azhar |
| Wersja dokumentu: | Drukowana | Elektroniczna |
| Arkusze wydawnicze: | 0,5 |
| Język: | angielski |
| Strony: | 289 - 297 |
| Web of Science® Times Cited: | 20 |
| Scopus® Cytowania: | 42 |
| Bazy: | Web of Science | Scopus | Web of Science Core Collection |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | TAK |
| Nazwa konferencji: | 16th Conference on Optical Fibers and their Applications |
| Skrócona nazwa konferencji: | 16th SPIE-IEEE-OFTA 2015 |
| URL serii konferencji: | LINK |
| Termin konferencji: | 22 września 2015 do 25 września 2015 |
| Miasto konferencji: | Nałęczów |
| Państwo konferencji: | POLSKA |
| Publikacja OA: | NIE |
| Abstrakty: | angielski |
| The second fundamental form (SFF) characterizes surface bending as value and direction of normal vector to surface. The value of SFF can be used for blur elimination by simple subtractions of the SFF from image signal. This operation narrows amplitude fronts saving contours as inflection lines. However, it sharpens all small fluctuations and introduces image distortion like noise. Therefore blur recognition and elimination using SFF has to be accompanied by procedure of image estimate optimization in accordance with regularization functional which acts as nonlinear filter. Two iterative methods of original image estimate optimization are suggested. The first method uses dynamic regularization basing on condition of iteration process convergence. The second method implements the regularization in curved space with metric defined on image estimate surface. The given iterative schemes have faster convergence in comparison with known ones |
