Journal of the Optical Society of America A · 2009 · 31 citations · 10 references
Natural SciencesEarth SciencesDigital Elevation ModelingRemote SensingTerrain AnalysisGeophysical InversionLidar Remote SensingA Posteriori AnalysisData InversionIll-posed Inverse ProblemsIll-posed Problem RegularizationIll-posed ProblemsLidar InversionRegularized InversionWaveform Decomposition
The retrieval of the backscatter cross section in lidar data is of great interest in remote sensing. For the numerical calculation of the backscatter cross section, a deconvolution has to be performed; its determination is therefore an ill-posed problem. Most of the common techniques, such as the well-known method of Gaussian decomposition, make implicit assumptions on both the emitted laser pulse and the scatterers. It is well understood that a land surface is quite complicated, and in many cases it cannot be composed of pure Gaussian function combinations. Therefore the assumption of Gaussian decomposition of waveforms may be invalid sometimes. In such cases an inversion method might be a natural choice. We propose a regularizing method with a posteriori choice of the regularizing parameter for solving the problem. The proposed method can alleviate difficulties in numerical computation and can suppress the propagation of noise. Numerical evidence is given of the success of the approach presented for recovering the backscatter cross section in lidar data.
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Solutions of Ill-Posed Problems.
John B. Bell, V. Y. Arsenin · Mathematics of Computation · 1978 · 8.2K citations
Wolfgang Wagner, Andreas Ullrich, V. Ducic et al. · ISPRS Journal of Photogrammetry and Remote Sensing · 2006 · 755 citations
Natural Sciences, Computational Engineering, Remote Sensing +11
VISUALIZATION AND ANALYSIS OF FULL-WAVEFORM AIRBORNE LASER SCANNER DATA
Åsa Persson, Ulf Söderman, Johanna Töpel et al. · 2005 · 126 citations