一种基于网格参数化的图像适应方法

图像适应是指将高分辨率的数字图像显示在手机、PDA等屏幕较小的显示终端上的过程.提出一种全新的基于网格参数化的图像适应方法,该方法的关键在于把图像表示为特征网格,从而将图像适应问题转化为网格的参数化,即求取一个与该特征网格同拓扑,且具有目标屏幕尺寸的网格.为了突出图像中的重要物体,该方法建立了源图像对应的特征网格与图像显著度的关系;通过优化基于显著度伸长的网格参数化的能量来求解适应图像的网格;然后借助纹理映射生成适应图像.另外,该方法在参数化的过程中增加了对显著区域和背景结构的约束,能够在保持并增强图像中重要物体的同时,使适应图像的结构不发生明显形变.该方法能够方便地处理具有复杂背景和包含多目标物体的图像的适应问题.实验结果显示了该方法的有效性.

A Mesh Parameterization-Based Image Retargeting Method

Image retargeting is the process of adapting images to display terminals with small sizes and different aspect ratios, such as cellular phones and PDAs. This paper presents a novel image retargeting method using saliency-based mesh parameterization. Specifically, this paper formulates retargeting an image to desired size as a constrained mesh parameterization problem which aims at finding a homomorphous target mesh with desired size. This method first constructs a mesh image representation that is consistent with the underlying image structures. To emphasize salient objects and minimize visual distortion, this paper associates image saliency into the mesh and defines image structure as mesh parameterization constraints. Through a stretch-based mesh parameterization process, this paper finally achieves the homomorphous target mesh, which is then used to render the target image by texture mapping. This method generates satisfactory retargeting effects for images with complex background structures. Also it works well for images with multiple salient objects. Experimental results demonstrate the effectiveness of the proposed method.