LDI tree: A hierarchical representation for image-based rendering

Using multiple reference images in 3D image warping has been a challenging problem. Recently, the Layered Depth Image (LDI) was proposed by Shade et ai. to merge multiple reference images under a single center of projection, while maintaining the simplicity of warping a single reference image. However it does not consider the issue of sampling rate. We present the LDI tree, which combines a hierarchical space partitioning scheme with the concept of the LDI. It preserves the sampling rates of the reference images by adaptively selecting an LDI in the LDI tree for each pixel. While rendering from the LDI tree, we only have to traverse the LDI tree to the levels that are comparable to the sampling rate of the output image. We also present a progressive refinement feature and a "gap filling" algorithm implemented by pre-filtering the LDI tree. We show that the amount of memory required has the same order of growth as the 2D reference images. This also bounds the complexity of rendering time to be less than directly rendering from all reference images.