IEEE Computer Graphics and Applications
Adaptive precision in texture mapping
SIGGRAPH '86 Proceedings of the 13th annual conference on Computer graphics and interactive techniques
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Prefetching in a texture cache architecture
HWWS '98 Proceedings of the ACM SIGGRAPH/EUROGRAPHICS workshop on Graphics hardware
Feline: fast elliptical lines for anisotropic texture mapping
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
HWWS '99 Proceedings of the ACM SIGGRAPH/EUROGRAPHICS workshop on Graphics hardware
Texture potential MIP mapping, a new high-quality texture antialiasing algorithm
ACM Transactions on Graphics (TOG)
Reconstruction filters in computer-graphics
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Constant-time filtering with space-variant kernels
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Texram: A Smart Memory for Texturing
IEEE Computer Graphics and Applications
SIGGRAPH '83 Proceedings of the 10th annual conference on Computer graphics and interactive techniques
Summed-area tables for texture mapping
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Footprint Area Sampled Texturing
IEEE Transactions on Visualization and Computer Graphics
High quality elliptical texture filtering on GPU
I3D '11 Symposium on Interactive 3D Graphics and Games
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We present a method to create high-quality sampling filters by combining a prescribed number of texels from several resolutions in a mipmap. Our technique provides fine control over the number of texels we read per texture sample so that we can scale quality to match a memory bandwidth budget. Our method also has a fixed cost regardless of the filter we approximate, which makes it feasible to approximate higher-quality filters such as a Lánczos 2 filter in real-time rendering. To find the best set of texels to represent a given sampling filter and what weights to assign those texels, we perform a cardinality-constrained least-squares optimization of the most likely candidate solutions and encode the results of the optimization in a small table that is easily stored on the GPU. We present results that show we accurately reproduce filters using few texel reads and that both quality and speed scale smoothly with available bandwidth. When using four or more texels per sample, our image quality exceeds that of trilinear interpolation.