Abstract:The aim of this study is to seek out the most suitable image fusion algorithm for OLI image of Landsat 8 satellite acquired in June 9, 2010, taking Yuyang country in Shaanxi Province as study area. Five kinds of image fusion algorithms have been employed, which are Brovey transform, High pass filter transform, HIS transform, PCA transform and LBV wavelet RF. The effectiveness of the five fusion algorithms has been evaluated based on spectral fidelity, high spatial frequency information gain, and supervised classification accuracy. Firstly, by visual evaluation this study evaluated whether fused images preserved spectral information of original multispectral image well, and whether retained texture and edges information of panchromatic image and avoided texture blurring. Secondly，by quantitative evaluation, spectrum character of fused images was analyzed by using gray average difference and gray root mean square error. Integration of the high frequency detail information of panchromatic images to fused images was analyzed by using correlation coefficient average and correlation root mean square error. The supervised classification accuracy of fused images was evaluated by using Kappa coefficient and overall classification accuracy. Results showed that LBV wavelet RF was the best method in retaining spectral information of original multispectral image, and not causing spectral distortion, as well as achieving the highest SVM supervised classification accuracy. Overall classification accuracy and Kappa coefficient of fused image using this method were 84.01% and 0.787，achieved noticeable growth of 13.45% and 15.91% than original multispectral image. The proposed OLI image fusion algorithm could provide far more detailed topographic information compared with original multispectral dates and better service for improving visual interpretation and supervised classification accuracy.
