The paper introduces a multiresolution spline technique for combining multiple images into a larger mosaic. The process involves decomposing the images into band-pass filtered component images, assembling these components into band-pass mosaics, and then summing the band-pass mosaic images to form the final mosaic. This method ensures that the spline is matched to the scale of features within the images, allowing for smooth transitions between images without blurring or degrading finer details near borders. The technique is demonstrated through various examples, including combining images of stars, Landsat photographs, and images of an apple and an orange. The paper also discusses the use of pyramid algorithms for efficient filtering and splining operations, highlighting the advantages of this approach in terms of computational efficiency and the ability to handle images of arbitrary shape.The paper introduces a multiresolution spline technique for combining multiple images into a larger mosaic. The process involves decomposing the images into band-pass filtered component images, assembling these components into band-pass mosaics, and then summing the band-pass mosaic images to form the final mosaic. This method ensures that the spline is matched to the scale of features within the images, allowing for smooth transitions between images without blurring or degrading finer details near borders. The technique is demonstrated through various examples, including combining images of stars, Landsat photographs, and images of an apple and an orange. The paper also discusses the use of pyramid algorithms for efficient filtering and splining operations, highlighting the advantages of this approach in terms of computational efficiency and the ability to handle images of arbitrary shape.