Ldi Tree : a Sampling Rate Preserving and Hierarchical Data Representation for Image - Based Rendering

Multiple reference images are required to eliminate disocclusion artifacts in image-based rendering based on McMillan's 3D image warping. Simply warping each individual reference image causes the rendering time to grow linearly with the number of reference images. This calls for a new data representation for merging multiple reference images. In this dissertation I present a hierarchical data representation, the LDI Tree, for merging reference images. It is distinguished from previous works by identifying the sampling rate issue and preserving the sampling rates of the reference images by adaptively selecting a suitable level in the hierarchy for each pixel. During rendering, the traversal of the LDI Tree is limited to the levels that are comparable to the sampling rate of the output image. This allows the rendering time to be driven by the requirements of output images instead of the number of input images. I also present a progressive refinement feature and a hole-filling algorithm implemented by pre-filtering the LDI Tree. I show that the amount of memory required has the same order of growth as the 2D reference images in the worst case. I also show that the rendering time depends mostly on the quality of the output image, while the number of reference images has a relatively small impact. iv To my wife, my parents, and my grandparents. v ACKNOWLEDGEMENTS