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Sparse PDF Maps for Non-linear Multi-resolution Image Operations

Abstract

We introduce a new type of multi-resolution image pyramid for high-resolution images called sparse pdf maps (sPDF-maps). Each pyramid level consists of a sparse encoding of continuous probability density functions (pdfs) of pixel neighborhoods in the original image. The encoded pdfs enable the accurate computation of non-linear image operations directly in any pyramid level with proper pre-filtering for anti-aliasing, without accessing higher or lower resolutions. The sparsity of sPDF-maps makes them feasible for gigapixel images, while enabling direct evaluation of a variety of non-linear operators from the same representation. We illustrate this versatility for antialiased color mapping, O(n) local Laplacian filters, smoothed local histogram filters (e.g., median or mode filters), and bilateral filters.

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Authors
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Supplemental Material
Citation
Category
Journal Paper
Divisions
Visualization and Data Analysis
Journal or Publication Title
ACM Transactions on Graphics
ISSN
0730-0301
Publisher
ACM
Place of Publication
New York, NY, USA
Page Range
133:1-133:12
Number
6
Volume
31
Date
November 2012
Official URL
http://doi.acm.org/10.1145/2366145.2366152
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