Name
Abstract | ||
|---|---|---|
In typical mosaicing or blending algorithms, it is usually assumed that the to-be-combined images are equally informative, and each component image would be processed in a similar manner. However, because of the photobleaching effect, the fluorescence intensity of confocal microscope image may degenerate; therefore, the overlapping regions will become asymmetrically informative. We formulate the problem of mosaicing such images as a multiscale optimization approach. The optimal blending coeffients can thus be obtained by a quadratic programming with constraints enforced by the biological requirements. We also demonstrate the efficacy on several confocal microscope fluorescence images as well as the EM images and compare the mosaicing results with those derived by other methods. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ISBI.2011.5872656 | 2011 8TH IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO |
Keywords | Field | DocType |
mosaicing, multiscale, optimization, confocal microscope image | Iterative reconstruction,Computer vision,Pattern recognition,Computer science,Image segmentation,Fluorescence intensity,Microscope,Artificial intelligence,Confocal,Quadratic programming,Microscopy,Image resolution | Conference |
ISSN | Citations | PageRank |
1945-7928 | 0 | 0.34 |
References | Authors | |
13 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hao-Chiang Shao | 1 | 9 | 4.97 |
| Wen-Liang Hwang | 2 | 429 | 58.03 |
| Yung-chang Chen | 3 | 799 | 96.73 |