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Cardinality-constrained texture filtering

Published:21 July 2013Publication History
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Abstract

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.

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  1. Cardinality-constrained texture filtering

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        cover image ACM Transactions on Graphics
        ACM Transactions on Graphics  Volume 32, Issue 4
        July 2013
        1215 pages
        ISSN:0730-0301
        EISSN:1557-7368
        DOI:10.1145/2461912
        Issue’s Table of Contents

        Copyright © 2013 ACM

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        Publication History

        • Published: 21 July 2013
        Published in tog Volume 32, Issue 4

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