基于三维几何视觉重要性的纹理图像选择压缩算法

不同于传统二维图像,映射到三维模型上的纹理图像隐式包含了三维几何视觉信息. 然而,目前已有的纹理图像压缩方法并未考虑此特性. 本文提出了一种与三维模型几何视觉特性相关的纹理图像选择压缩算法. 首先给出一种结合纹理图像的显著性及其纹理走样的视觉重要性图构建方法, 将纹理图像划分为具有不同优先级别区域.之后,利用提出的选择压缩方法对它们进行不同比例压缩. 实验结果表明当选择本压缩算法时,纹理化三维模型能够获取较好的视觉效果.

Selective Compression for Texture Map Image Based on Visual Importance from 3D Geometry

Different from common 2D images, when a texture map image is project to a 3D model in the 3D space, it also implicitly associates with certain 3D geometry information. However, existing common texture map image compression methods do not take this into account. In this paper, we present a visual importance driven selective compression method for texture map image. Firstly, a visual important map construction method is presented, which takes not only the saliency information of the texture image but also the distortion of texture mapping into account. With this visual importance map, the texture map image is divided into several distinct areas. Then, the selective compression method is presented to compress these areas with a varying compression ratio. Experimental results show that the textured 3D model can obtain a better visual result when adopting our method.