This paper presents a multiresolution-based image fusion technique using additive wavelet decomposition to merge high-resolution panchromatic images with low-resolution multispectral images. The method improves upon standard intensity-hue-saturation (IHS) and LHS merging techniques by preserving both spectral and spatial information. The approach involves adding the high-order wavelet coefficients of the panchromatic image to the intensity component (L = (R + G + B)/3) of the multispectral image. The "à trous" algorithm is used for wavelet decomposition, allowing the use of a dyadic wavelet to merge non-dyadic data such as SPOT and LANDSAT images. The method is applied to merge SPOT and LANDSAT (TM) images, resulting in better preservation of spectral characteristics compared to IHS and LHS methods. The additive wavelet method on the L component (AWL) is found to be the most effective, as it preserves the multispectral image's spectral content while enhancing spatial resolution. The AWL method is considered an improvement over IHS and LHS methods because it does not substitute the intensity component but instead adds high-resolution information to the multispectral image's intensity component. The method is efficient and simple, using the same dyadic wavelet for merging images of any resolution. The results show that the AWL method achieves higher correlation with the original multispectral image compared to standard methods, indicating better preservation of spectral characteristics. The method is suitable for applications in remote sensing, astronomy, and other fields requiring high-resolution image fusion.This paper presents a multiresolution-based image fusion technique using additive wavelet decomposition to merge high-resolution panchromatic images with low-resolution multispectral images. The method improves upon standard intensity-hue-saturation (IHS) and LHS merging techniques by preserving both spectral and spatial information. The approach involves adding the high-order wavelet coefficients of the panchromatic image to the intensity component (L = (R + G + B)/3) of the multispectral image. The "à trous" algorithm is used for wavelet decomposition, allowing the use of a dyadic wavelet to merge non-dyadic data such as SPOT and LANDSAT images. The method is applied to merge SPOT and LANDSAT (TM) images, resulting in better preservation of spectral characteristics compared to IHS and LHS methods. The additive wavelet method on the L component (AWL) is found to be the most effective, as it preserves the multispectral image's spectral content while enhancing spatial resolution. The AWL method is considered an improvement over IHS and LHS methods because it does not substitute the intensity component but instead adds high-resolution information to the multispectral image's intensity component. The method is efficient and simple, using the same dyadic wavelet for merging images of any resolution. The results show that the AWL method achieves higher correlation with the original multispectral image compared to standard methods, indicating better preservation of spectral characteristics. The method is suitable for applications in remote sensing, astronomy, and other fields requiring high-resolution image fusion.