Parallel Gradient Domain Processing of Massive Images
Sujin Philip, Brian Summa, Peer-Timo Bremer, Valerio Pascucci
Eurographics Symposium on Parallel Graphics and Visualization, 2011, pp. 11--19.
Abstract: Gradient domain processing remains a particularly computationally expensive technique even for relatively small images. When images become massive in size, giga or terapixel, these problems become particularly troublesome and the best serial techniques take on the order of hours or days to compute a solution. In this paper, we provide a simple framework for the parallel gradient domain processing. Specifically, we provide a parallel out-of-core method for the seamless stitching of gigapixel panoramas in a parallel MPI environment. Unlike existing techniques, the framework provides both a straightforward implementation, maintains strict control over the required/allocated resources, and makes no assumptions on the speed of convergence to an acceptable image. Furthermore, the approach shows good weak/strong scaling from several to hundreds of cores and runs on a variety of hardware.
@inproceedings{Philip:2011:PGD,
author = {Sujin Philip and Brian Summa and Peer-Timo Bremer and Valerio Pascucci},
title = {Parallel Gradient Domain Processing of Massive Images},
booktitle = {Eurographics Symposium on Parallel Graphics and Visualization},
pages = {11--19},
year = {2011},
}
Return to the search page.
graphbib: Powered by "bibsql" and "SQLite3."