SuperpixelSurvey.pdf (8.92 MB)

A survey of superpixel methods and their applications

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posted on 2023-07-20, 02:39 authored by Chong WuChong Wu, Hong YAN

Superpixels can preserve the structure and reduce the redundancy of the original image. Because of these advantages, superpixel generation or superpixel segmentation is widely used as a pre-processing step in many image processing tasks. Although superpixels can be employed to reduce computational complexity, some challenges, such as the non-Euclidean feature learning problem introduced by superpixels, still exist. This survey provides a comprehensive overview of the state-of-the-art superpixel methods, major challenges, commonly used evaluation metrics, applications of superpixels, and potential future directions for the study of superpixels. We first give a review of the state-of-the-art superpixel methods. Next, we use different evaluation metrics to evaluate the performance of 24 up-to-date superpixel methods on different datasets in different noisy environments. After that, we introduce several up-to-date applications of superpixels. Finally, we give several possible future directions for addressing the challenges of superpixels.


Hong Kong Innovation and Technology Commission (InnoHK Project CIMDA)

Hong Kong Research Grants Council (Project 11204821)

City University of Hong Kong (Projects 9610034 and 9610460)


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Submitting Author's Institution

Department of Electrical Engineering and Centre for Intelligent Multidimensional Data Analysis, City University of Hong Kong

Submitting Author's Country

  • China

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