基于高阶LLF和WENO算法的透视SFS  

Perspective shape from shading based on high-order LLF and WENO

作　　者：王学梅[1] 孙即祥[1] 

机构地区：[1]国防科技大学电子科学与工程学院,长沙410073

出　　处：《中国图象图形学报》2011年第2期300-304,共5页Journal of Image and Graphics

摘　　要：透视投影下从明暗恢复形状(SFS)问题,通常通过结合静态Hamilton-Jacobi(HJ)方程和快速扫描方法来求解。为进一步优化静态HJ方程的求解精度,改善透视SFS的恢复结果,采用了高阶局部Lax-Friedrichs(LLF)通量分裂格式,以提高待求量的偏导数的精度;同时采用了改进的加权本质无振荡(WENO)格式,使得算法只计算整格点值,并且利用修正的光滑因子得到比WENO更高的精度。对合成图像和实际图像的实验结果表明,可以有效提高透视投影SFS问题的恢复精度。Perspective shape from shading can be solved by combining static Hamihon-Jacobi （H J） equation and fast sweeping method. To optimize the solution of static HJ equation and improve the results of perspective shape from shading, this paper uses high-order local Lax-Friedrichs（LLF） flux splitting scheme to increase the accuracy of partial derivatives. Besides, the paper uses modified weighted essentially non-oscillatory（WENO） scheme, which only uses integer grids and gets higher accuracy than WENO by using amended smoothness estimators. Experiments of synthetic and real images demonstrate that the algorithm can obtain accurate results for perspective SFS.

关 键 词：从明暗恢复形状 静态HJ方程 快速扫描法 局部Lax—Friedrichs 加权本质无振荡 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]