This project deals with resizing an image, while keeping the most important information in the image. The method uses seam carving. First a cost map of the image is created using either gradients or other filters, this provies knowledge in the image as to where the most important parts (read: highest frequency) of the image are. The program then uses dynamic programming to find the path of 8 connected pixels (one per row or column) which follows the lowest cost. This seam of pixels is removed and the image is resized accordingly.

Contents:
Images that were seperately resized in the X and Y direction.
Images that were diagonally resized using an optimized combination of the X and Y seam cutting.
Images that performed poorly when resized.
All images were found on Google Image search or Flickr