Publikation
Sparse PDF Maps for Non-Linear Multi-Resolution Image Operations
Jens Krüger; Markus Hadwiger; Ronell Sicat; Johanna Beyer; Torsten Möller
In: Julie Dorsey (Hrsg.). ACM Transactions on Graphics (TOG), Vol. 31, Pages 133:1-133:12, ACM, 2012.
Zusammenfassung
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.