@article{7d5034897a6e4abf83ef905a17827865,
title = "Surface Reconstruction and Image Enhancement via $L^1$-Minimization",
abstract = "A surface reconstruction technique based on minimization of the total variation of the gradient is introduced. Convergence of the method is established, and an interior-point algorithm solving the associated linear programming problem is introduced. The reconstruction algorithm is illustrated on various test cases including natural and urban terrain data, and enhancement oflow-resolution or aliased images. Copyright {\textcopyright} by SIAM.",
author = "Veselin Dobrev and Jean-Luc Guermond and Bojan Popov",
note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledged KAUST grant number(s): KUS-C1-016-04 Acknowledgements: Received by the editors March 26, 2009; accepted for publication ( in revised form) February 12, 2010; published electronically June 9, 2010. This material is based upon work supported by the National Science Foundation grants DMS-0510650 and DMS-0811041. This publication is based on work partially supported by Award KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST). This publication acknowledges KAUST support, but has no KAUST affiliated authors.",
year = "2010",
month = jan,
doi = "10.1137/09075408X",
language = "English (US)",
volume = "32",
pages = "1591--1616",
journal = "SIAM Journal on Scientific Computing",
issn = "1064-8275",
publisher = "Society for Industrial and Applied Mathematics Publications",
number = "3",
}