Evaluating the effect of band subset selection in SLIC superpixel segmentation

Author(s):  
Pavithra Pochamreddy ◽  
Mohammed Alkhatib ◽  
Miguel Velez-Reyes
1988 ◽  
Author(s):  
Shanti S. Gupta ◽  
TaChen Liang

2019 ◽  
Author(s):  
Elshadai Tesfaye Biru ◽  
Yishak Tofik Mohammed ◽  
David Tofu ◽  
Erica Cooper ◽  
Julia Hirschberg

2019 ◽  
Vol 5 (6) ◽  
pp. 57 ◽  
Author(s):  
Gang Wang ◽  
Bernard De Baets

Superpixel segmentation can benefit from the use of an appropriate method to measure edge strength. In this paper, we present such a method based on the first derivative of anisotropic Gaussian kernels. The kernels can capture the position, direction, prominence, and scale of the edge to be detected. We incorporate the anisotropic edge strength into the distance measure between neighboring superpixels, thereby improving the performance of an existing graph-based superpixel segmentation method. Experimental results validate the superiority of our method in generating superpixels over the competing methods. It is also illustrated that the proposed superpixel segmentation method can facilitate subsequent saliency detection.


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