中文摘要：

针对传统基于网格变形的图像缩放技术中可能出现的主体对象大小会随图像缩放而缩放的问题,提出一种既考虑网格形状,又考虑网格大小的形变量度量模型.在图像重要度约束下,通过简单的参数调整让用户选择性地控制主体对象的大小.重新定义图像重要度模型为梯度和显著度的加权平均,这样既考虑到人眼对图像的视觉关注,又考虑到对图像中结构信息的有效保护.在计算显著度时,改进基于稀疏特征的单分辨率模型为多分辨率模型,从而有效地保留了高分辨率下的边缘信息和低分辨率下的区域内部信息.实验结果表明,文中方法能更精确地识别出图像中的主体对象,并能在缩放时根据用户需求控制主体对象大小,同时很好地保持图像的重要特征.

英文摘要：

Traditionally,the mesh-based image resizing has a limitation that prominent objects in an image will always be reduced or magnified along with the image reducing or enlarging.In this paper,a new measurement model about quad distortion energy by considering both the quad＇s shape and size is proposed to avoid such disadvantage.Moreover,a significance map is redefined as the weighted average of image gradient and saliency,in which both the structural and perceptual information are considered.Finally,single resolution based visual attention model which is calculated from the rarity of features is improved to be a multi-resolution model.It can combine the merits of that the visual attention model is sensitive to the edge of prominent object in the higher resolution and to the interior region of the prominent object in the lower resolution.Testing with many images,we demonstrate that the proposed approach achieves superior accuracy significance map and can change the primary object＇s size adapting to user preference while preserves the image prominent features.