Similarity criterion for image resizing

Based on bidirectional similarity measure between patches of image, in this study, we investigate the similarity criterion of image for resizing image. First, our scheme implements image resizing by Seam Carving step by step. For each step, we remove five seams, and then calculate the dissimilarity between the original image and its resized one as well as the relative difference of dissimilarity between neighboring steps. According to the relative differences of dissimilarity of all steps, we can assess the degree of distortion of the resized image and conclude the similarity criterion. On the basis of the similarity criterion, we present an effective image-resizing algorithm by combining Seam Carving, Scaling, and Bidirectional Similarity iteration. Before the salient feature gets damaged markedly, we change the resizing method from Seam Carving to Scaling, and resize the image up to the preferred size. Then, we can update the resized image to eliminate artifacts by iterative computations of Bidirectional Similarity measure. Experiments show that, even though the amount of adjustment is large, our algorithm can preserve the important information, local structures, and global visual effect adequately.