Numerous approaches can be utilized for image enlargement, among them seam-carving, texture-synthesis, linear scaling and warping are commonly used. However, all of these methods have their disadvantages. In this paper, we propose a new image enlargement method inspired from seam-carving and texture synthesis, called Patch-Based Seam Synthesis. Our algorithm fully utilizes the texture information of an image and thus is a content-based method. The procedure of this new method is described as follows. Firstly, we use a set of Difference of Gaussian (DOG) and Difference of Offset Gaussian (DOOG) filters to extract the texture features of the image. Secondly, we use the Histogram Shape-Based Image Thresholding to divide the image into texture regions and non-texture regions. Thirdly, we find the energy map of the image based on the energy function and determine the minimal-energy seams, the 8-connected paths crossing the whole image, either vertically or horizontally. Finally, we use patch-based synthesis combined with image quilting algorithm to fill in the parts of the seams that are in the texture regions and linear interpolation to smooth the parts that lie in non-texture regions.
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