Developing a new IHS-based fusion methodology for GeoEye-1 satellite imagery with the ELSHORA fusion technique

Abstract

In this research, a new image fusion technique was developed to merge the spatial details in the panchromatic (PAN) image and the spectral details in the multispectral (MS) image to produce fused images with the highest spatial and spectral qualities. This fusion technique is superior to the other existing fusion techniques in that it can produce sharp images with no color distortion for all types of land cover. This is because of using weighting parameters for all MS bands in the calculation of the I component according to the intersecting areas between the MS bands and the PAN band, and the I component will be an average of the four modified MS bands, which minimizes the gray level differences between PAN and I images. Moreover, using the variable vegetation coefficient β for the NIR band makes this technique produce the highest spectral and spatial qualities for each land cover class. To evaluate the performance of the ELSHORA fusion technique, it was compared to the traditional intensity-hue-saturation (IHS) fusion technique, the fast IHS (FIHS) fusion technique, and four other standard image fusion techniques; principal component analysis, hyper-spherical color space, multiplicative resolution merge and Brovey transform. These fusion techniques were applied to three sets of GeoEye-1 PAN and MS images covering different land covers in Tanta city, Egypt. The fused images are compared statistically and visually to the original PAN and MS images. The results showed that the ELSHORA fusion technique was chosen as the best method for all datasets. This is because it has produced the highest spectral quality in which no color distortion can be detected and has provided significant spatial quality, visually and analytically. To test the spatial and temporal transferability of ELSHORA fusion technique, it was compared to the original FIHS fusion technique to fuse three different datasets covering different classes of land cover (urban, agriculture, and mixed) located in different places and acquired at different times. The results indicate that ELSHORA fusion technique is spectrally and spatially in the lead for all datasets. This study proved the efficiency of ELSHORA fusion technique to produce images of high spectral and spatial resolution at different times and places.