SURFACE RECONSTRUCTION AND IMAGE ENHANCEMENT VIA L-1-MINIMIZATION Academic Article

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 by SIAM.

authors

• Popov, Bojan

published proceedings

• SIAM JOURNAL ON SCIENTIFIC COMPUTING

author list (cited authors)

• Dobrev, V., Guermond, J., & Popov, B.

citation count

• 6

complete list of authors

• Dobrev, Veselin||Guermond, Jean-Luc||Popov, Bojan

publication date

• January 2010

publisher

• Society for Industrial & Applied Mathematics (SIAM)  Publisher

published in

• SIAM Journal on Scientific Computing  Journal

keywords

• Data Reconstruction
• Digital Elevation Models
• Finite Elements
• Image Enhancement
• Interior-point Algorithm
• L-1-minimization

Digital Object Identifier (DOI)

• 10.1137/09075408X

URI

• https://hdl.handle.net/1969.1/185465

start page

• 1591

end page

• 1616

volume

• 32

issue

• 3

URL

• http://dx.doi.org/10.1137/09075408x