@techreport{sar-sto-lei-atk-smi-11-msintg-tr,
  author = {Rafael Saracchini and Jorge Stolfi and Helena C. G. Leit{\~a}o and Gary A. Atkinson and Melvyn L. Smith},
  title = {Multi-Scale Integration of Slope Data on an Irregular Mesh},
  month = may,
  year = 2011,
  institution = {Institute of Computing, University of Campinas},
  number = {IC-11-11},
  note = {In English},
  pages = {19},
  citations = {WoS/2021: 1},
  abstract = {We describe a fast and robust method for computing scene depths (or heights) from surface gradient (or surface normal) data, such as would be obtained by photometric stereo or interferometry. Our method allows for uncertain or missing samples, which are often present in experimentally measured gradient maps; for sharp discontinuities in scene's depth, e~.g.~along object silhouette edges; and for irregularly spaced sampling points. To accomodate these features of the problem, we introduce an original and flexible representation of slope data, the weigth-delta mesh. Like other state of the art solutions, our algorithm reduces the problem to a system of linear equations that is solved by Gauss-Seidel iteration with multi-scale acceleration. Tests with various synthetic and measured gradient data show that our algorithm is as accurate and efficient as the best available integrators for uniformly sampled data. Moreover, thanks to the use of the weight-delta mesh representation, our algorithm remains accurate and efficient even for large sets of weakly-connected data, which cannot be efficiently handled by any existing algorithm.}
}