Subimage selection from multiple images with joint singular value decomposition for segmentation

Toru Hiraoka, Kiichi Urahama

Research output: Contribution to journalArticle

Abstract

Pixel clustering is a basic process in image segmentation for classifying various regions in an image. However, this clustering becomes complex for multispectral and hyperspectral images due to the high dimensionality of these images. For such cases, dimensionality reduction is usually used to remove component images unsuitable for pixel clustering, in order to reduce computaional cost and improves accuracy. We propose a simple dimensionality reduction method in which a subset of component images is selected from multiple images using the joint singular value decomposition. Results of experiments for LandsatTM multispectral images demonstrate the effectiveness of the proposed method. Segmentation using a subimage chosen by the proposed enables us to avoid mixture of inappropriate component images and improve the performance of the segmentation.

Original languageEnglish
JournalKyokai Joho Imeji Zasshi/Journal of the Institute of Image Information and Television Engineers
Volume66
Issue number9
DOIs
Publication statusPublished - Sep 10 2012

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Singular value decomposition
Pixels
Image segmentation
Costs
Experiments

All Science Journal Classification (ASJC) codes

  • Media Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

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