Bilinear interpolation and use of perceptual color spaces (HSL, HSV, LAB, and LUV) fusion techniques are presented to improve spatial and spectral characteristics of the multispectral image that has a low resolution to match the high spatial resolution of a panchromatic image for different satellites image data (Orbview-3 and Landsat-7) for the same region. The Signal-to-Noise Ratio (SNR) fidelity criterion for achromatic information has been calculated, as well as the mean color-shifting parameters that computed the ratio of chromatic information loss of the RGB compound inside each pixel to evaluate the quality of the fused images. The results showed the superiority of HSL color space to fuse images over the rest of the spaces, as it recorded the highest SNR and the lowest mean color-shifting. The quality of the fused images using Lab color space was not affected by the type of intermediate algorithm used for XYZ space, unlike LUV color space. The XYZ algorithm type affected the fused image results, which recorded the worst consequences. It is noted that the computational time taken increased exponentially with the difference in spatial resolution between the fused images.
