Power-SLIC: Diagram-based superpixel generation
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Superpixel algorithms, which group pixels similar in color and other low-level properties, are increasingly used for pre-processing in image segmentation. Commonly important criteria for the computation of superpixels are boundary adherence, speed, and regularity. Boundary adherence and regularity are typically contradictory goals. Most recent algorithms have focused on improving boundary adherence. Motivated by improving superpixel regularity, we propose a diagram-based superpixel generation method called Power-SLIC. On the BSDS500 data set, Power-SLIC outperforms other state-of-the-art algorithms in terms of compactness and boundary precision, and its boundary adherence is the most robust against varying levels of Gaussian noise. In terms of speed, Power-SLIC is competitive with SLIC.
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