Handling non-linearity between classes using spectral and spatial information with kernel based modified possibilistic c-means classifier-Reference-Cited by-同舟云学术

Handling non-linearity between classes using spectral and spatial information with kernel based modified possibilistic c-means classifier

Published:2020-07-30 Issue: Volume: Page:1-18
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Chhapariya Koushikey¹,Kumar Anil¹,Upadhyay Priyadarshi²

Affiliation:

1. Photogrammetry and Remote Sensing Department, Indian Institute of Remote Sensing, Indian Space Research Organisation, Department of Space, Government of India, Dehradun, India

2. Uttarakhand Space Application Centre, Department of Information & Science Technology, Government of Uttarakhand, Dehradun, India

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2020.1797186

Reference24 articles.

1. FCM: The fuzzy c-means clustering algorithm

2. Composite Kernels for Hyperspectral Image Classification

3. Chawla S. 2010. Possibilistic C-means - spatial contextual information based sub-pixel classification approach for multi-spectral data. The Netherlands: University of Twente, p. 1–89.

4. Gaussian Kernel Based Fuzzy C-Means Clustering Algorithm for Image Segmentation

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