The paper presents a technique for merging high-resolution panchromatic and low-resolution multispectral images using multiresolution wavelet decomposition. The method involves adding the wavelet coefficients of the high-resolution image to the intensity component of the multispectral image, specifically defined as \( L = \frac{R + G + B}{3} \). This approach is compared with standard intensity-hue-saturation (IHS) and lightness (LHS) methods, which often degrade spectral characteristics. The "à trous" algorithm is used for wavelet decomposition, allowing the method to handle non-dyadic data efficiently. The study demonstrates that the additive wavelet method on the L component (AWL) outperforms other methods in preserving both spectral and spatial information, making it an improvement over traditional IHS and LHS techniques. The method is applied to merge SPOT and LANDSAT (TM) images, showing better correlation with the original multispectral data and preserving the spatial quality of the multispectral image while enhancing its spectral content.The paper presents a technique for merging high-resolution panchromatic and low-resolution multispectral images using multiresolution wavelet decomposition. The method involves adding the wavelet coefficients of the high-resolution image to the intensity component of the multispectral image, specifically defined as \( L = \frac{R + G + B}{3} \). This approach is compared with standard intensity-hue-saturation (IHS) and lightness (LHS) methods, which often degrade spectral characteristics. The "à trous" algorithm is used for wavelet decomposition, allowing the method to handle non-dyadic data efficiently. The study demonstrates that the additive wavelet method on the L component (AWL) outperforms other methods in preserving both spectral and spatial information, making it an improvement over traditional IHS and LHS techniques. The method is applied to merge SPOT and LANDSAT (TM) images, showing better correlation with the original multispectral data and preserving the spatial quality of the multispectral image while enhancing its spectral content.