Name
Abstract | ||
|---|---|---|
Typical mosaicing schemes assume that to-be-combined images are equally informative; thus, the images are processed in a similar manner. However, the new imaging technique for confocal fluorescence images has revealed a problem when two asymmetrically informative biological images are stitched during microscope image mosaicing. The latter process is widely used in biological studies to generate a higher resolution image by combining multiple images taken at different times and angles. To resolve the earlier problem, we propose a multiresolution optimization approach that evaluates the blending coefficients based on the relative importance of the overlapping regions of the to-be-combined image pair. The blending coefficients are the optimal solution obtained by a quadratic programming algorithm with constraints that are enforced by the biological requirements. We demonstrate the efficacy of the proposed approach on several confocal microscope fluorescence images and compare the results with those derived by other methods. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TBME.2011.2175446 | IEEE Trans. Biomed. Engineering |
Keywords | Field | DocType |
biomedical optical imaging,image resolution,multiresolution optimization approach,confocal microscope image,fluorescence,confocal microscope fluorescence image,blending coefficient,a quadratic programming algorithm,image optimal multiresolution blending,mosaicing,blending,medical image processing,microscopy,vectors,biology,quadratic program,optimization,fluorescence imaging,laplace equation,asymmetric information | Computer vision,Computer science,Microscope,Artificial intelligence,Microscopy,Confocal,Quadratic programming,Image resolution | Journal |
Volume | Issue | ISSN |
59 | 2 | 1558-2531 |
Citations | PageRank | References |
0 | 0.34 | 18 |
Authors | ||
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 |