Image Quality Assessment for Fused Remote Sensing Imageries
DOI:
https://doi.org/10.11113/jt.v71.3839Keywords:
Image fusion, hyperspectral, image qualityAbstract
Image fusion provides precise information in both spatial and spectral resolutions that benefit significantly in high accuracy mapping. Yet, there is less intention withdrawn in justifying the performance of the fused image. In this study, qualitative and quantitative assessments were carried out to test the quality of fusion image. Principal Component Analysis (PCA), Gram-Schmidt and Ehlers were applied to fuse the hyperspectral and Lidar image. Ehlers fusion showed good in preserving the color of image and contained the most information. Besides, the classification of Ehlers fused image showed the highest accuracy.References
J. Zhang. 2010. Int. J. Image and Data Fusion. 1 : 5–24.
C. Pohl, J.L.Van Genderen. 1998. Int. J. Remote Sensing. 19 : 823–854.
D. Jiang, D. Zhuang, et al. 2011. Image Fusion and Its Applications. 1.
H. Liu and X. Zhang. 2009. Urban Remote Sensing Event. 1–6.
D. Chao, H. Li, J. Han. 2011. Advances in Computer Science, Intelligent System and Environment, Springer. 104 : 169–173.
S. Klonus, M. Ehlers. 2009. Int. Conf. on Information Fusion. 1409–1416.
A.K. Helmy, A.H. Nasr, et al. 2010. Int. J. Computer. 4 : 107–115.
K.Kotwal, S. Chaudhuri. 2013. Information Fusion. 14 : 5–18.
D. Jiang, D. Zhuang, et al. 2009. Sensors. 9 : 7771–7784.
D. Amarsaikhan, H.H. Blotevogel, et al. 2010. Int. J. Image and Data Fusion. 1 : 83–97.
M. Fallah Yakhdani, A. Azizi. 2010. ISPRS Conf. Vienna. XXXVIII : 204–209.
Downloads
Published
Issue
Section
License
Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.
