6533b824fe1ef96bd1280b6b

RESEARCH PRODUCT

Sparsity-Driven Digital Terrain Model Extraction

Erdal YilmazGustau Camps-vallsFatih Nar

subject

FOS: Computer and information sciencesHardware_MEMORYSTRUCTURES010504 meteorology & atmospheric sciencesIterative methodComputer scienceComputer Vision and Pattern Recognition (cs.CV)0211 other engineering and technologiesComputer Science - Computer Vision and Pattern RecognitionTerrain02 engineering and technologyFunction (mathematics)Hardware_PERFORMANCEANDRELIABILITYComputerSystemsOrganization_PROCESSORARCHITECTURES01 natural sciencesData setHardware_INTEGRATEDCIRCUITSExtraction (military)Digital elevation modelAlgorithm021101 geological & geomatics engineering0105 earth and related environmental sciences

description

We here introduce an automatic Digital Terrain Model (DTM) extraction method. The proposed sparsity-driven DTM extractor (SD-DTM) takes a high-resolution Digital Surface Model (DSM) as an input and constructs a high-resolution DTM using the variational framework. To obtain an accurate DTM, an iterative approach is proposed for the minimization of the target variational cost function. Accuracy of the SD-DTM is shown in a real-world DSM data set. We show the efficiency and effectiveness of the approach both visually and quantitatively via residual plots in illustrative terrain types.

yearjournalcountryeditionlanguage
2020-12-07
https://aperta.ulakbim.gov.tr/record/29071