Earth observation satellites provide multispectral images that are characterized by good spectral quality but low spatial quality. They also provide panchromatic images that, on the contrary, are characterized by good spatial quality but low spectral quality. Therefore, it is important to merge both images to obtain a single one that contains complementary information and can be used in land resource studies, surface geology, water management, forests, urban development, agriculture, and others. For this reason, it is important to evaluate the techniques used for the fusion of multispectral and panchromatic images: EIHS, Brovey and Averaging. Therefore, in this work these three techniques are evaluated, using the quantitative indices: spectral ERGAS and spatial ERGAS. In this way, the quality of the resulting fused images can be measured. Natural images were used to make the evaluation. The results show, on the one hand, that the best spectral quality is obtained with the Averaging algorithm, followed by the Brovey and, thirdly, by the EIHS. On the other hand, the best spatial quality was obtained with the EIHS algorithm, followed by the Brovey and then by the Averaging algorithm. It was also found that by averaging the values obtained in both evaluations that the best quality of fusion is obtained with the Averaging algorithm, followed by the Brovey and finally by the EIHS.