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28 October 2006A method of edge detection based on improved canny algorithm for the lidar depth image
Edge-detection of LIDAR depth-image is an important work for further image analysis. Based on the theory of Canny
algorithm, this paper discusses insufficiencies of Canny operator and proposes an improved method. Instead of using
Gaussian smoothing filter, the improved algorithm carries on the smoothing operation by an adaptive median filter for
the characteristics of LIDAR depth-image. As a result, it can not only eliminate noises effectively but also protect
unclear edges. Gradient computation and determination of edge points are also improved, gradient magnitudes of pixels
are calculated with first-order derivatives within eight neighborhoods instead of four, and the precision of edge location
is enhanced consequently. Considering the deficiency of uniform threshold for the whole image in Canny operator and
its non-objectivity in determining threshold values, the improved algorithm divides image into a number of sub-images
and detects edges with adaptive threshold values respectively. Therefore, edge points with low height values are
protected and adaptation of the algorithm is also improved. Datasets from urban areas were selected to test this
algorithm. The results show that the improved algorithm can make up for the disadvantages of canny algorithm, and can
detect edges of LIDAR depth-images effectively.
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Jingzhong Xu, Youchuan Wan, Xubing Zhang, "A method of edge detection based on improved canny algorithm for the lidar depth image," Proc. SPIE 6419, Geoinformatics 2006: Remotely Sensed Data and Information, 64190O (28 October 2006); https://doi.org/10.1117/12.712923