Article Per Year (5 Year)
p-Index From 2019 - 2024
0
P-Index
This Author published in this journals
All Journal Indonesian Journal of Electrical Engineering and Computer Science
Lipeng Gao
China University of Mining and Technology

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
A New Framework of the Unsupervised Classification for High-Resolution Remote Sensing Image Penglin Zhang; Zhiyong Lv; Lipeng Gao
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 7: November 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Classification plays a significant role in change detection when monitoring the evolution of the Earth’s surface. This paper proposes a novel object-oriented framework for the unsupervised classification of high-resolution remote sensing images based on Jenks’ optimization. The fractal net evolution approach is employed as an image segmental technique, the spectral feature of each image object is extracted, and an algorithm of Jenks’ optimization is adopted as a classifier. Two experiments with different image platforms are conducted to evaluate the performance of the proposed framework and to compare with other traditional unsupervised classification algorithms such as the iterative self-organizing data analysis technique algorithm and k-means clustering algorithms. The proposed approach is found to be feasible and valid. DOI: http://dx.doi.org/10.11591/telkomnika.v10i7.1571
Co-Authors Penglin Zhang Zhiyong Lv