NDLI: Segmentation of SAR images using similarity ratios for generating and clustering superpixels

Content Provider	IET Digital Library
Author	Akyilmaz, E. Leloglu, U. M.
Abstract	The superpixels are groups of similar neighbouring pixels which are perceptually meaningful and representationally efficient segments. Among those existing superpixel generating algorithms, simple linear iterative clustering (SLIC) seems to be one of the simplest ones. Its simplicity is due to adaption of a distance measure which is a linear combination of colour and spatial proximity. It is this measure that is modified using a similarity ratio. This modified measure is used to label the pixels within the search areas for generating the superpixels. This generation phase is further augmented with a clustering phase based on the same formulated similarity metric, which clusters the superpixels into larger segments. It has been demonstrated that this modified version performs better in terms of boundary recall and undersegmentation error, and is more robust to the speckle noise than the one in SLIC. Moreover, the clustered segments formed by superpixels generated by this approach has better boundary adherence than those formed by superpixels generated by SLIC.
Starting Page	654
Ending Page	656
Page Count	3
ISSN	00135194
Volume Number	52
e-ISSN	1350911X
Issue Number	Issue 8, Apr (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/52/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2016.0020
Journal	Electronics Letters
Publisher Date	2016-03-14
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Boundary Adherence Boundary Recall Colour And Spatial Proximity Linear Combination Image Colour Analysis Image Segmentation Interpolation And Function Approximation Iterative Method Numerical Analysis Optical, Image And Video Signal Processing Pattern Clustering Radar Equipment Radar Imaging Radar Theory SAR Image Segmentation Similarity Ratios Simple Linear Iterative Clustering Algorithm SLIC Algorithm Superpixel Clustering Superpixel Generation Synthetic Aperture Radar System And Application Undersegmentation Error
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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