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Schlagwörter:
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Zusammenfassung:
Image Pyramids, as created during a reduction process of 2D image maps, are
frequently used in porting non-local algorithms to graphics hardware. A
Histogram pyramid (short: HistoPyramid), a special version of image pyramid,
collects the number of active entries in a 2D image. We show how a HistoPyramid
can be utilized as an implicit indexing data structure, allowing us to convert
a sparse 3D volume into a point cloud entirely on the graphics hardware. In the
generalized form, the algorithm reduces a highly sparse matrix with N elements
to a list of its M active entries in O(N) + M (log N) steps, despite the
restricted graphics hardware architecture. Our method can be used to deliver
new and unusual visual effects, such as particle explosions of arbitrary
geometry models. Beyond this, the algorithm is able to accelerate feature
detection, pixel classification and binning, and enable high-speed sparse
matrix compression.