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The Mean Shift procedure is a well established clustering technique that is widely used in imaging applications such as image and video segmentation, denoising, object tracking, texture classification, and others. However, the Mean Shift procedure has relatively high time complexity which is superlinear in the number of data points. In this paper we present a novel fast Mean Shift procedure which...
National forest inventories (NFI) are essential for countrywide estimations of a wide range of forest functions. Our research aim is to derive measurable forest features out of airborne image data by using automatic computer-vision based methods. This paper focuses on tree layer detection of high resolution ADS40 data for automation. Preliminary experimental results of mean-shift segmentation method...
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