基于缝裁剪和变形的图像缩放方法

提出一种既能保持图像重要内容又能较好地保持重要物体形状的图像缩放算法。该方法结合传统的缝裁剪技术和变形技术来对图像进行缩放。首先利用当前公认效果良好的基于图模型的流形排序显著性检测算法得到图像的显著度图,结合图像梯度能量等信息来构造结构更为清晰的图像重要度图；其次利用之前构造的图像重要度图并按缩放尺度的大小来确定适当的缩放方法；最后根据度量比较结果来选择经典缝裁剪方法或基于能量优化的变形方法进行图像缩放。对比实验结果表明,该方法在图像缩放时能保持重要内容和显著物体形状结构。

Image Resizing Based on Seam Carving and Warping

This paper presented an image resizing method which can preserve the content and the shape of salient objects.Image can be resized by using traditional seam carving and warping techniques.First,the proposed method produces the significant map of clear shape and structure by combining the saliency detection via graph-based manifold ranking and gradient energy information.And then appropriate resizing methods are determined according to the size of the resizing scale by using the former significant map.Finally,image can be resized by the classic seam carving method or the resizing method of deformation based on energy optimization according to the comparison results.A lot of comparison results show that the method can keep both important content and shape and structure of salient objects.