A Sparsity-Based Regularization Approach for Deconvolution of Full-Waveform Airborne Lidar Data
نویسندگان
چکیده
منابع مشابه
A Sparsity-Based Regularization Approach for Deconvolution of Full-Waveform Airborne Lidar Data
Full-waveform lidar systems capture the complete backscattered signal from the interaction of the laser beam with targets located within the laser footprint. The resulting data have advantages over discrete return lidar, including higher accuracy of the range measurements and the possibility of retrieving additional returns from weak and overlapping pulses. In addition, radiometric characterist...
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As an active remote sensing technique airborne laser scanning (ALS) is able to capture the topography with high precision even for densely forested areas. Due to the high pulse repetition frequency of up to 400 kHz a high sampling rate on the ground can be achieved, which allows the description of the terrain surface in decimeter scale. In this contribution two approaches to characterize terrai...
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The lack of noise reduction methods resistant to waveform distortion can hamper correct and accurate decomposition in the processing of full-waveform LiDAR data. This paper evaluates a time-domain method for smoothing and reducing the noise level in such data. The Savitzky-Golay (S-G) approach approximates and smooths data by taking advantage of fitting a polynomial of degree d, using local lea...
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2016
ISSN: 2072-4292
DOI: 10.3390/rs8080648