Spectral and Spatial Quality Analysis in Pan Sharpening Process

Ayhan E., Atay G.

JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, cilt.40, sa.3, ss.379-388, 2012 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 40 Sayı: 3
  • Basım Tarihi: 2012
  • Doi Numarası: 10.1007/s12524-011-0185-0
  • Dergi Adı: JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.379-388
  • Anahtar Kelimeler: Image fusion, Pan sharpening, Brovey method, PCA method, Wavelet PC method, Wavelet ATrous method, Ikonos, Spectral evaluation, Spatial evaluation, MULTISENSOR IMAGE FUSION, DISCRETE WAVELET TRANSFORM, RESOLUTION IMAGES, SATELLITE IMAGES, ARSIS CONCEPT
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

Image fusion is a process to obtain new images containing more information by combining images obtained same or different sensors. With most of the earth observation satellites, high spatial resolution panchromatic images and low spatial resolution multispectral images are obtained. As an example of image fusion "pan sharpening" is a process of combining of high spatial resolution panchromatic images and low spatial resolution multispectral images. At the end of the fusion process both high spatial and spectral resolution new images are obtained. In this study, panchromatic and multispectral images gathered from Ikonos were used. Panchromatic and multispectral images belonging to the same sensor were combined by using different image fusion methods. As pan sharpening methods Brovey transform, Modified IHS, Principal Component Analysis (PCA), Wavelet PC transform and Wavelet A Trous transformation methods were used. Quality of fused products was evaluated from the point of view of both visual and statistical criteria. While wavelet based methods are succesfull in terms of protection of spectral quality of original multispectral images, the colorbased and statistical methods are giving better results within the improvement of spatial content.