[IPOL announce] new article: Bilateral K-Means for Superpixel Computation (the SLIC Method)

[announcements about the IPOL journal]

A new article is available in IPOL: https://www.ipol.im/pub/art/2022/373/

Robin Gay, Jérémie Lecoutre, Nicolas Menouret, Arthur Morillon, and 
Pascal Monasse,
Bilateral K-Means for Superpixel Computation (the SLIC Method),
Image Processing On Line, 12 (2022), pp. 72–91.
https://doi.org/10.5201/ipol.2022.373

Abstract
As a substitute to a full segmentation of a digital image, or as 
preprocessing to a segmentation algorithm, superpixels provide an 
over-segmentation that offers several benefits: good adherence to edges, 
uniformity of color inside superpixels, a richer adjacency structure 
than the regular grid of pixels, and the fact that each node of the 
graph of superpixels has a shape, which can be used in subsequent 
processing. Moreover, their evaluation is less subjective than a full 
segmentation, which somehow always involves a semantic interpretation of 
the scene. The SLIC method (Simple Linear Iterative Clustering) has been 
a very popular algorithm to compute superpixels since its introduction. 
Its advantage is due to its simplicity and to its computing time 
performance. In essence, it consists in a K-means clustering in 
bilateral domain, involving both position and color. We study in detail 
this algorithm and propose a fast, simple post-processing that ensures 
that superpixels are connected, a property not ensured by the original 
method.