Image fusion involves integration of the geometric details of a high-resolution panchromatic (PAN) image and the spectral information of a low resolution multispectral (XS) image which is useful for regional planning and large scale urban mapping. Present study compares the effectiveness of three image fusion techniques namely, Principal Component Analysis (PCA), Wavelet Transform (WT) and Intensity Hue Saturation (IHS) to merge the XS information and PAN data of QuickBird satellite imagery. Comparison between the fused images obtained from the three fusion techniques is carried out on the basis of qualitative and quantitative evaluations implying, visual interpretation, inter-band correlation, correlation coefficient, standard deviation and mean. Results indicate that all three fusion techniques improves spatial resolution as well as spectral details, however, IHS technique provides the best spectral fidelity by preserving the XS integrity between all the bands under consideration.

The article compares the effectiveness of three image fusion techniques: Principal Component Analysis (PCA), Wavelet Transform (WT) and Intensity Hue Saturation (IHS).

Performance of each technique is evaluated through quantitative and qualitative techniques.

The PCA and Wavelet fusion techniques cause distortions and make the photo-interpretation more difficult.

IHS technique provides the best spectral fidelity by preserving the XS integrity between all the bands under consideration.