【摘要】 在基于模型的编码技术中，选择合适的网格模型对提高模型的运动估计精度、编码效率和得到高质量的解码图像都是至关重要的．文中提出的基于图像内容的自适应网格模型生成算法，首先利用数学形态学中的水线算法把编码图像分割成许多纹理一致的区域，所分割的区域反映了图像的结构、轮廓和边界；再对这些区域的边界进行多边形拟合，得到多边形各个边的端点作为网格模型的节点，以这些节点为基础就能生成一个 Ｄｅｌａｕｎａｙ 三角形网格．通过该算法得到的网格能有效的描述编码图像的结构，从而有更好的运动补偿能力和更高的编码效率更多还原

【Abstract】 It is critical to choose a suitable model for accurate motion estimation, efficiently encoding image signal, and high quality decoding image in model based coding. A content based adaptive mesh generation algorithm is proposed in this paper. At first, a watershed algorithm of mathematical morphology is used to segment image into many homogeneous regions so that watershed lines can better represent image structure, contours, and edges. Boundaries of these regions are approximated by polygons that can be represented with a few parameters. Each end point of polygonal sides serves as candidate node of mesh model. Because interval between candidate nodes may be too large or small, some mesh elements based on these nodes are unsuitable for later tracking and motion estimation in quality and size. Some preprocessing are adopted to delete or insert some candidate nodes. A content based Delaunay triangular mesh can be generated on these nodes with limitation in nodal interval. The results of this algorithm can more efficiently represent encoding image structure, so accurate motion estimation and efficiently encoding can better achieve in model based coding.更多还原