A method of enhancing an image comprising: increasing sampling rate of a first image to a target sampling rate to form an interpolated image; processing a second image through a high pass filter to form a high pass features image, wherein the second image is at the target sampling rate; extracting detail from the high pass features image; merging the detail from the high pass features image with the interpolated image to form a prediction image at the target sampling rate; and outputting the prediction image; wherein extracting detail from the high pass features image is done on a segment by segment basis from the high pass features image for use in merging with the interpolated image, wherein extracted detail for each segment is governed by individualized prediction coefficients; and wherein extracting detail includes receiving an image segmentation map for segmenting the high pass features image and receiving prediction coefficients corresponding to respective segments of the image segmentation map for extracting detail on a segment by segment basis; characterised in that receiving the image segmentation map and receiving the prediction coefficients includes receiving the image segmentation map and prediction coefficients from a training operation, wherein the training operation includes: creating a reduced sampling rate copy of the second image; processing the reduced sampling rate copy of the second image and the first image through a high pass filter to form second and first feature images (134,136), respectively; processing the reduced sampling rate copy of the second image and the first image through a segmentation operation to produce the segmentation map; and processing the first and second feature images (134;136) and the segmentation map through a fit process to generate the prediction coefficients; and wherein extracting detail from the high pass features image includes increasing the sampling rate of the segmentation map to the target sampling rate. increasing sampling rate of a first image to a target sampling rate to form an interpolated image; processing a second image through a high pass filter to form a high pass features image, wherein the second image is at the target sampling rate; extracting detail from the high pass features image; merging the detail from the high pass features image with the interpolated image to form a prediction image at the target sampling rate; and outputting the prediction image; wherein extracting detail from the high pass features image is done on a segment by segment basis from the high pass features image for use in merging with the interpolated image, wherein extracted detail for each segment is governed by individualized prediction coefficients; and wherein extracting detail includes receiving an image segmentation map for segmenting the high pass features image and receiving prediction coefficients corresponding to respective segments of the image segmentation map for extracting detail on a segment by segment basis; characterised in that receiving the image segmentation map and receiving the prediction coefficients includes receiving the image segmentation map and prediction coefficients from a training operation, wherein the training operation includes: creating a reduced sampling rate copy of the second image; processing the reduced sampling rate copy of the second image and the first image through a high pass filter to form second and first feature images (134,136), respectively; processing the reduced sampling rate copy of the second image and the first image through a segmentation operation to produce the segmentation map; and processing the first and second feature images (134;136) and the segmentation map through a fit process to generate the prediction coefficients; and wherein extracting detail from the high pass features image includes increasing the sampling rate of the segmentation map to the target sampling rate. creating a reduced sampling rate copy of the second image; processing the reduced sampling rate copy of the second image and the first image through a high pass filter to form second and first feature images (134,136), respectively; processing the reduced sampling rate copy of the second image and the first image through a segmentation operation to produce the segmentation map; and processing the first and second feature images (134;136) and the segmentation map through a fit process to generate the prediction coefficients; and wherein extracting detail from the high pass features image includes increasing the sampling rate of the segmentation map to the target sampling rate.