dc.contributor.authorWang, Lin
dc.description.abstractLight Detection and Ranging is a new and hot remote sensing technology for many applications, including self-driving cars and navigation. It can also be used to generate digital terrain models. The airborne LIDAR system usually returns a 3-D cloud of irregular spacing point measurements called the raw LIDAR dataset. In order to generate a digital terrain model, it is necessary to measure the characteristics of unwanted objects such as vehicles, trees that all need to be deleted and classified. This project is to study some effective data and image processing techniques for better earth surface mapping and sensing. It is a pure software project and both MATLAB and C++ computing languages will be used for algorithm testing and fast computation purpose. In this report, the basic and the progressive morphological filter are used to delete unwanted LIDAR points. By choosing adequate parameters, the unwanted objects were deleted, while the needed measurement could be remained. But for different morphological filters, the computing efficiency is quite different. Thus, in this report, three methods are applied for progressive morphological filter. By comparison these methods, it can be selected for multiple type of dataset and can choose which programming approach is more effective.en_US
dc.format.extent59 p.en_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleLidar data processing for enhanced earth surface mapping and sensingen_US
dc.contributor.supervisorLu Yilongen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Communications Engineering)en_US

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