Theoretical Analysis of View Interpolation With Inaccurate Depth Information
A problem of view interpolation from a pair of rectified stereo images with inaccurate depth information is addressed. Errors in geometric information greatly affect the quality of the resulting images since inaccurate geometry causes miscorrespondences between the input images. A new theory for quantitatively analyzing the effect of depth errors and providing a principled optimization scheme based on the mean-squared error metric is proposed. The theory clarifies that, if the probabilistic distribution of the depth errors is given, an optimized view-interpolation scheme that outperforms conventional linear interpolation can be derived. It also reveals that, under specific conditions, linear interpolation is acceptable as an approximation of the optimized-interpolation scheme. Furthermore, band limitation combined with linear interpolation is also analyzed, leading to an optimal cutoff frequency, which achieves better results than the antialias scheme proposed in previous studies. Experimental results using real scenes are also presented to confirm this theory.