A Sparsity Analysis of Light Field Signal For Capturing Optimization of Multi-view Images

In the previous results, light field sampling is based on ideal assumptions (e.g., Lambertian and Non-occluded scene), and thus we would like to more precisely analyze the sparsity sampling of light field signal. We present a sparsity analysis of light field (SALF) method for optimizing light field sampling rate. The SALF method applies the Fourier projection-slice theorem to simplify the initialization of light field sampling. Furthermore, we use a voting scheme to select light field spectra in which the frequency coefficients are nonzero. These spectra include many scene information and their captured positions are approximately equal to camera positions in the frequency domain. If the camera is only placed in these selected camera positions, the sampling rate can be optimized and the rendering quality can be guaranteed. Finally, we compare SALF method with other light field sampling methods to verify the claimed performance. The reconstruction results show that the SALF method improves rendering quality of novel views and outperforms those of other comparison methods.