Compression of structured 3-D model geometry with multiresolution decomposition by decoded coefficient prediction

In this paper, we propose a new compression method for geometry data of 3-D mode using decoded coefficient prediction based on the structuring of surrounding vertices. We have proposed the structuring procedure of surrounding 3-D vertices on a 2-D plane to obtain 2-D structured geometry data. In this paper, multiresolution decomposition by decoded coefficient prediction decomposes structured geometry data in consideration of correlations between adjacent vertices. The decomposition processing gives four components in one step according to where each vertex is located in the structured geometry data and the prediction is performed. In the prediction process, the predicted value is obtained from decoded coefficients of the processed vertices adjacent to the target vertex in the polygonal mesh. Experimental results show that the proposed method gives better coding performance, in particular at higher coding rates, than conventional coding methods.