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论文类型：期刊论文

发表时间：2012-01-01

发表刊物：EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING

收录刊物：SCIE、EI、Scopus

卷号：2012

期号：1

页面范围：1-11

ISSN号：1687-5281

关键字：image resizing; similarity measure; SIFT feature; Seam Carving; Scaling

摘要：On the basis of the Scale Invariant Feature Transform (SIFT) feature, we research the distance measure in the process of image resizing. Through extracting SIFT features from the original image and the resized one, respectively, we match the SIFT features between two images, and calculate the distance for SIFT feature vectors to evaluate the degree of similarity between the original and the resized image. On the basis of the Euclidean distance measure, an effective image resizing algorithm combining Seam Carving with Scaling is proposed. We first resize an image using Seam Carving, and calculate the similarity distance between the original image and its resized one. Before the salient object and content are damaged obviously, we stop Seam Carving and transfer residual task to Scaling. Experiments show that our algorithm is able to avoid the damage and distortion of image content and preserve both the local structure and the global visual effect of the image graciously.