Abstract: When gray images are magnified, the smoothing effect of gray level interpolation may degrade the fine details in images and make contours become blurred. An interpolation magnification algorithm for gray images based on the fitted dividing curves is presented. This algorithm includes two stages: segmentation and interpolation magnification. In the segmentation stage, the abrupt transition pixels in the image are extracted and fitted as cubic uniform B-spline. This process results in fitted dividing curves and is used to divide the whole image into several subimages. In interpolation magnification stage, the interpolation operation is limited to inside a subimage. This magnification operation eliminates the common zigzag and blurred effect occurred in conventional magnified images and keeps the contours of magnified image still sharp and smooth.