Effects of image fusion on the information capacity of ZY-3 imagery

Ningyu Zhang; Junqing Zhao; Xuan Liu; Shuang Li

doi:10.1117/12.2244964

29 August 2016 Effects of image fusion on the information capacity of ZY-3 imagery

Ningyu Zhang, Junqing Zhao, Xuan Liu, Shuang Li

Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 1003320 (2016) https://doi.org/10.1117/12.2244964
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China

Abstract

The modified image fusion methods are developed for merging ZY-3 remote sensing images. The main objective of this research is to study the effects of image fusion, based on the information capacity of panchromatic and multispectral ZY-3 images. The image fusion techniques include PCA transform, BT transform, G-S transform, and HSV transform. The experimental results show that the spatial resolution of images merged by PCA, BT G-S and HSV transforms is higher than the original ZY-3 image, and these four transforms techniques merge the features of the panchromatic and multispectral images very well. However, the hue of the HSV merged image is different from the original image, which indicates HSV led to obvious color distortion. The hue of the PCA merged image is also approximately the same as for the original image, without image distortion. Furthermore, the discussion of the information capacity considers quantity in terms of the spectral authenticity and the entrop, which indicates images merged by PCA showing higher spatial resolution and better spectral features, compared with images merged by the other three transforms. Although losing some spectral information, images merged by HSV also showed higher spatial resolution. Therefore, PCA is very efficient and highly accurate for merging ZY-3 images.

Citation Download Citation

Ningyu Zhang, Junqing Zhao, Xuan Liu, and Shuang Li "Effects of image fusion on the information capacity of ZY-3 imagery", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 1003320 (29 August 2016); https://doi.org/10.1117/12.2244964

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