• Vandana Tripathi

This paper demonstrates the implementation and usefulness of multi-scale transform based pan-sharpening technique for urban information extraction. Multi-scale Transform (MST) based image analysis techniques overcome the shortcomings of the conventional Fourier-based, purely spatial and frequency based techniques. MST provides the efficient characterization of local spectral properties of non stationary image which is desirable for pan-sharpening. The pan sharpening techniques namely, Discrete Wavelet Transform (DWT), Stationary Wavelet Transform (SWT) and Non sub-sampled contour-let Transform (NSCT) techniques have been selected for the pan-sharpening of multispectral images of World View-2 and IKONOS sensors. The accuracy of the pan sharpening techniques has been evaluated by means of standard parameters, such as, Root Mean Square Error, Peak Signal-to-Noise Ratio, Correlation Coefficient, ERGAS and UIQI. Experimental analysis proves that NSCT based pan-sharpening technique gives good result in terms of urban information and have a good trade-off between the preservation of spectral information and the enhancement of spatial resolution.

Pan-sharpening, Multi-scale Transform analysis, Non Sub-sampled Contour-let Transform.

"Pan-Sharpening of Multi-Spectral Satellite Image Using Multi-Scale Transform Based Techniques For Urban Information Extraction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.507-515, June-2019, Available :http://www.jetir.org/papers/JETIR1906E26.pdf

"Pan-Sharpening of Multi-Spectral Satellite Image Using Multi-Scale Transform Based Techniques For Urban Information Extraction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp507-515, June-2019, Available at : http://www.jetir.org/papers/JETIR1906E26.pdf