@inproceedings {503,
	title = {Multiresolution Network Flow Phase Unwrapping},
	booktitle = {IEEE 2000 International Geoscience and Remote Sensing Symposium},
	year = {2000},
	abstract = {<p>Phase unwrapping is a key step in deriving topographic information from interferometric SAR. Several recent methods are based on a minimum cost network flow approach. The authors develop a new, computationally efficient, ldquo;divide-and-conquer rdquo; strategy for phase unwrapping</p>
},
	keywords = {divide and conquer methods, divide-and-conquer method, geophysical measurement technique, geophysical techniques, InSAR, interferometric SAR, land surface topography, multiresolution network flow phase unwrapping, phase unwrapping, radar remote sensing, radar theory, remote sensing by radar, synthetic aperture radar, terrain mapping, topography (Earth)},
	doi = {http://dx.doi.org/10.1109/IGARSS.2000.861693},
	author = {G F Carballo and P Fieguth}
}
@inproceedings {511,
	title = {Foveated multiscale models for large-scale estimation},
	booktitle = {International Conference on Image Processing},
	year = {1999},
	abstract = {<p>Efficient, large-scale estimation methods such as nested dissection or multiscale estimation rely on a divide-and-conquer strategy, in which a statistical problem is conditionally broken into smaller pieces. This conditional decorrelation is not possible for arbitrarily large problems due to issues of computational complexity and numerical stability. Given the growing interest in global-scale-remote sensing problems (or even three-dimensional problems), in this summary we develop a class of estimators with more promising asymptotic computational properties</p>
},
	keywords = {asymptotic computational properties, computational complexity, conditional decorrelation, decorrelation, divide and conquer methods, divide-and-conquer strategy, foveated multiscale models, global-scale-remote sensing problems, image processing, large-scale estimation methods, multiscale estimation, nested dissection, numerical stability, statistical problem, three-dimensional problems},
	doi = {http://dx.doi.org/10.1109/ICIP.1999.823022},
	author = {P Fieguth}
}
