Surface Reconstruction and Image Enhancement via $L^1$-Minimization
KAUST Grant NumberKUS-C1-016-04
Permanent link to this recordhttp://hdl.handle.net/10754/599816
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AbstractA 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 © by SIAM.
CitationDobrev V, Guermond J-L, Popov B (2010) Surface Reconstruction and Image Enhancement via $L^1$-Minimization. SIAM Journal on Scientific Computing 32: 1591–1616. Available: http://dx.doi.org/10.1137/09075408X.
SponsorsReceived 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).