Sparse PDF maps for non-linear multi-resolution image operations
| Autor: | Jens Krüger, Torsten Möller, Johanna Beyer, Ronell Sicat, Markus Hadwiger |
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| Rok vydání: | 2012 |
| Předmět: |
Pixel
business.industry Mipmap ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Anti-aliasing Computer Graphics and Computer-Aided Design Image (mathematics) Informatik Encoding (memory) Color mapping Computer vision Pyramid (image processing) Bilateral filter Artificial intelligence business Mathematics |
| Zdroj: | ACM Transactions on Graphics. 31:1-12 |
| ISSN: | 1557-7368 0730-0301 |
| DOI: | 10.1145/2366145.2366152 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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