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

Toru Hiraoka, Kiichi Urahama

    Research output: Contribution to journalArticlepeer-review


    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
    Pages (from-to)J322-J325
    JournalKyokai Joho Imeji Zasshi/Journal of the Institute of Image Information and Television Engineers
    Issue number9
    Publication statusPublished - 2012

    All Science Journal Classification (ASJC) codes

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


    Dive into the research topics of 'Subimage selection from multiple images with joint singular value decomposition for segmentation'. Together they form a unique fingerprint.

    Cite this