BBAuthors: Csillik, O.; Advisor: -; Participants: - (2016)
In computer vision, using superpixels or perceptually meaningful atomic regions to speed up later-stage processing are becoming increasingly popular in many applications. Superpixels are used as a pre-processing stage to organize an image into a low-level grouping process through oversegmentation, thus simplifying the computation in later stages. However, in remote sensing domain few studies use superpixels. Even so, there is no comparison between superpixel methods and their suitability for remote sensing images. In this study, we compare four state-of-the-art superpixel methods: Simple Linear Iterative Clustering (SLIC and SLICO), Superpixels Extracted via Energy-Driven Sampling (SE... 
