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The use of task queue image partitioning makes these optimizations efficient in a parallel framework.
Estimation of this spatio-temporal surface is formulated as a Bayesian image partitioning problem.
We have designed a parallel volume rendering algorithm for MIMD architectures based on ray tracing and a novel task queue image partitioning technique.
A novel quad-tree based image partitioning technique is also developed in this work for effective feature extraction from the numeric digit patterns.
Ground truth is collected via a novel random sampling scheme for color, and by an image partitioning method for texture.
Knee et al. [16] used image partitioning and sparse representation based feature to handle SAR target recognition.
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The framework includes three parts: auto image partition, two-stage grouping and two-layer classification.
Finally, an efficient multi-objective clustering paradigm in AIS and kernel mapping thereof to implement final image partition is proposed.
The image foresting transform (IFT) reduces optimal image partition problems based on seed pixels to a shortest-path forest problem in a graph, whose solution can be obtained in linear time.
Therefore, sub-block image partitions are different.
(a) Image partitioned into 16 blocks.
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