一种从离散法线图重建高度图的方法

A Method for Reconstructing a Height Map From a Discrete Normal Map

阴影形状、偏转测量和光度立体法等多种手段都能得到场景的法线场,需要进一步重建才能获得高度场,因此由法线场重建场景的深度信息值得研究。提出一种由离散法向量恢复高度场函数的方法。首先,基于离散几何的原理,逐行估计场景的行高度值;然后计算少量列高度;最后根据列高度值,逐行调整各行的高度平均值,得出整个场景的高度分布,其中在估计行高度值与列高度值的过程都运用了最小二乘法。该方法由于减少了优化的数据量,不需要大型的矩阵运算和运算内存,并且对于物体表面连续并且光滑的曲面会有较好的效果。实验表明,该方法对曲面连续突变较少的场景的深度恢复较好,但对于突变较多的场景,所恢复出的高度会有横条纹。

The normal field of the scene can be obtained by various methods such as shadow shape,deflection measurement and photometric stereo.The height field function obtained from the normal field plays an important role in 3D reconstruction methods such as shadow shape and photometric stereo,so the depth information of the scene reconstructed from the normal field is worth studying.A method to recover height field function from discrete normal vector is proposed in this paper.Firstly,based on the principle of discrete geometry,the row height value of the scene is estimated line by line.Then,a small number of column heights are calculated.Finally,according to the column height value,the average height of each row is adjusted row by row to obtain the height distribution of the whole scene.The least square method is used in the process of estimating the row height value and column height value.This method reduces the amount of optimization data.It does not need large matrix operations and operation memory,and has a good effect on the surface of the object,which is continuous and smooth.Experimental results show that the depth recovery of the scene with few continuous surface mutations is better,but for the scene with many mutations,the recovered height will have horizontal stripes.