Sparse PDF maps for non-linear multi-resolution image operations
Type
Conference Paper
KAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionComputer Science Program
Visual Computing Center (VCC)
Date
2012-11-01Permanent link to this record
http://hdl.handle.net/10754/575790Metadata
Show full item recordAbstract
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. © 2012 ACM.Citation
Hadwiger, M., Sicat, R., Beyer, J., Krüger, J., & Möller, T. (2012). Sparse PDF maps for non-linear multi-resolution image operations. ACM Transactions on Graphics, 31(6), 1–12. doi:10.1145/2366145.2366152Journal
ACM Transactions on GraphicsConference/Event name
Proceedings of ACM SIGGRAPH Asia 2012Scopus Count
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