مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

video

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

sound

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Version

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View:

1,002
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

0
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Cites:

Information Journal Paper

Title

DIMENSIONALITY REDUCTION OF HYPERSPECTRAL IMAGES VIA BANDS FUZZY CLUSTERING

Pages

  467-478

Abstract

 This paper proposes an innovative BAND SELECTION method based on fuzzy clustering of bands for HYPERSPECTRAL IMAGES.The main novelties of this research lie in two issues: i) bands representation in a new space called PROTOTYPE SPACE (PS) where bands take characteristic vector in terms of class reflectivity (where bands' feature vectors are defined in terms of class reflectivity), and ii) using uncertainty and angle measures to distinguish highly correlated and informative channels. Having clustered channels by Fuzzy C-Means (FCM) clustering in PS, the highly correlated bands fall in a cluster by uncertainty measure, then a nearest band to the cluster center is discerned as representative of those bands. Moreover uncertain bands as isolated bands are separated in PS where among isolated bands the bands that have large angle with diagonal of PS are indicated as informative channels. Since finding representative and informative bands depends on random initialization of FCM clustering, the bands clustering algorithm conducted many times. Accordingly, the proper bands are selected by maximizing overall accuracy of validation data set. Benchmarking on the challenging hyperspectral data set demonstrated relative merit of proposed method respect to the conventional BAND SELECTION methods like sequential forward floating and sequential backward floating BAND SELECTION.

Cites

  • No record.
  • References

  • No record.
  • Cite

    APA: Copy

    MOIARRADI, B., VALADANZOUJ, M.J., & ABRISHAMI MOGHADAM, H.. (2009). DIMENSIONALITY REDUCTION OF HYPERSPECTRAL IMAGES VIA BANDS FUZZY CLUSTERING. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TEHRAN), 43(4 (122)), 467-478. SID. https://sid.ir/paper/357946/en

    Vancouver: Copy

    MOIARRADI B., VALADANZOUJ M.J., ABRISHAMI MOGHADAM H.. DIMENSIONALITY REDUCTION OF HYPERSPECTRAL IMAGES VIA BANDS FUZZY CLUSTERING. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TEHRAN)[Internet]. 2009;43(4 (122)):467-478. Available from: https://sid.ir/paper/357946/en

    IEEE: Copy

    B. MOIARRADI, M.J. VALADANZOUJ, and H. ABRISHAMI MOGHADAM, “DIMENSIONALITY REDUCTION OF HYPERSPECTRAL IMAGES VIA BANDS FUZZY CLUSTERING,” JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TEHRAN), vol. 43, no. 4 (122), pp. 467–478, 2009, [Online]. Available: https://sid.ir/paper/357946/en

    Related Journal Papers

    Related Seminar Papers

  • No record.
  • Related Plans

  • No record.
  • Recommended Workshops






    Move to top
    telegram sharing button
    whatsapp sharing button
    linkedin sharing button
    twitter sharing button
    email sharing button
    email sharing button
    email sharing button
    sharethis sharing button