Efficient methods for tile-based synthesis and computational photography

This thesis presents contributions to two major topics in computer graphics. The first part describes new algorithms for tile-based synthesis of blue noise point sets and solid textures; the second part describes systems for capturing, viewing, and manipulating outdoor photographs. Well distributed point sets play an important role in computer graphics, as well as many other fields, since they lie in the very foundation of any sampling technique. Many previous researchers have pointed out that point sets with a blue noise Fourier spectrum, i.e. the points are distributed both evenly and randomly, are desirable in many applications. In this thesis, we introduce a novel technique for rapidly generating such point sets. Through the use of Wang tiles, our technique deterministically generates infinite non-periodic patterns. Any local area may be consistently regenerated as needed. The points in each tile form a progressive sequence, enabling matching arbitrary spatially varying point densities. Recursion allows our technique to adaptively subdivide tiles where high density is required, and makes it possible to zoom into point sets by an arbitrary amount, while maintaining a constant apparent density. The technique is extremely fast (point generation is in the order of several millions of points per second) and has a compact memory footprint. These properties make our technique highly suitable for a variety of real-time interactive applications, some of which are demonstrated in this thesis. Another area where tiling techniques are commonly utilized is texture synthesis. While 2D texture synthesis has been heavily researched in the past decade, synthesis of high quality solid textures remained a mostly unsolved problem. We present a novel method for synthesizing solid textures from 2D texture exemplars. First, we extend 2D texture optimization techniques to synthesize 3D texture solids. Next, the non-parametric texture optimization approach is integrated with histogram matching, which forces the global statistics of the synthesized solid to match those of the exemplar. This approach improves the convergence speed of the synthesis process and the quality of the synthesized results drastically. Our method is applicable to a wide variety of textures, including anisotropic textures, textures with large coherent structures, and multi-channel textures.