High-efficiency texture coding and synthesis on point-based pear surface

© 2017 IOS Press and the authors. The fruit images on points cloud acquired by the current 3D scanner from field will appear a visible seams, inconvenient data acquisition or taking large space due to unorganized background. We give a SAOW method to cope with the space efficiency and realistic effects of texture synthesis on pear point model. At first, a point-quadtree is proposed to simplify the pear image division. Then, an adaptive multi-granularity morton coding scheme are presented to optimizing the memory space of pear image. At last, weighted oversampling mixing method is mainly focused on texture quality of pear surface. As shown in the experiment results, our adaptive division makes the memory space decline dramatically about 90.7% than non-division and 92.9% than general division respectively; adaptive code scheme helps to reduce the memory to 72.1% of ordinary morton code; weighted oversampling keeps the mixed texture more real and smoothly than current methods

A separate least squares algorithm for efficient arithmetic coding in lossless image compression

The overall performance of discrete wavelet transforms for losssless image compression may be further improved by properly designing efficient entropy coders. In this paper a novel technique is proposed for the implementation of context-based adaptive arithmetic entropy coding. It is based on the prediction of the value of the current transform coefficient. The proposed algorithm employs a weighted least squares method applied separately for the HH, HL and LH bands of each level of the multiresolution structure, in order to achieve appropriate context selection for arithmetic coding. Experimental results illustrate and evaluate the performance of the proposed technique for lossless image compression