Multilevel thresholding hyperspectral image segmentation based on independent component analysis and swarm optimization methods

Murinto, Murinto and Pujiastuti, Nur Rochmah Dyah and Mardhia, Murein Miksa (2019) Multilevel thresholding hyperspectral image segmentation based on independent component analysis and swarm optimization methods. [Artikel Dosen]

[thumbnail of HASIL CEK_Murinto_Multilevel thresholding hyperspectral image segmentation based on independent component analysis and swarm optimization methods.pdf]

Text
HASIL CEK_Murinto_Multilevel thresholding hyperspectral image segmentation based on independent component analysis and swarm optimization methods.pdf
Download (2MB)

Official URL: http://ijain.org/index.php/IJAIN

Abstract

High dimensional problems are often encountered in studies related to
hyperspectral data. One of the challenges that arise is how to find
representations that are accurate so that important structures can be cleared
easily. This study aims to process segmentation of hyperspectral image by
using swarm optimization techniques. This experiments use Aviris Indian
Pines hyperspectral image dataset that consist of 103 bands. The method
used for segmentation image is particle swarm optimization (PSO),
Darwinian particle swarm optimization (DPSO) and fractional order
Darwinian particle swarm optimization (FODPSO). Before process
segmentation image, the dimension of the hyperspectral image data set are first reduced by using independent component analysis (ICA) technique to get first independent component. The experiments show that FODPSO method is better than PSO and DPSO, in terms of the average CPU processing time and best fitness value. The PSNR and SSIM values when using FODPSO are better than the other two swarm optimization
methods. It can be concluded that FODPSO has better in order to obtain
segmentation results compared to the previous method.

Item Type:	Artikel Dosen
Keyword:	Darwinian particle swarm Optimization FODPSO Hyperspectral Image Multi-level thresholding Particle swarm optimization
Subjects:	Q Science > Q Science (General)
Divisi / Prodi:	Faculty of Industrial Technology (Fakultas Teknologi Industri) > S1-Informatics Engineering (S1-Teknik Informatika)
Depositing User:	murinto murinto
Date Deposited:	18 Apr 2023 09:44
Last Modified:	23 Sep 2023 06:41
URI:	http://eprints.uad.ac.id/id/eprint/42976

Actions (login required)

View Item