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Summary: Edge-Based Image Coarsening
Raanan Fattal
Hebrew University of Jerusalem, Israel
Robert Carroll
University of California, Berkeley
Maneesh Agrawala
University of California, Berkeley
This paper presents a new dimensionally-reduced linear image space that allows a number of re-
cent image manipulation techniques to be performed efficiently and robustly. The basis vectors
spanning this space are constructed from a scale-adaptive image decomposition, based on kernels
of the bilateral filter. Each of these vectors locally binds together pixels in smooth regions and
leaves pixels across edges independent. Despite the drastic reduction in the number of degrees of
freedom, this representation can be used to perform a number of recent gradient-based tonemap-
ping techniques. In addition to reducing computation time, this space can prevent the bleeding
artifacts which are common to Poisson-based integration methods. In addition, we show that this
reduced representation is useful for energy-minimization methods in achieving efficient processing
and providing better matrix conditioning at a minimal quality sacrifice.
Categories and Subject Descriptors: I.3.3 [Computer Graphics]: Picture/Image Generation,
Display algorithms
General Terms: Algorithms
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