Abstract
The integral histogram is a recently proposed preprocessing technique to compute histograms of arbitrary rectangular gridded (i.e. image or volume) regions in constant time. We formulate a general parallel version of the the integral histogram and analyse its implementation in Star Superscalar (StarSs). StarSs provides a uniform programming and runtime environment and facilitates the development of portable code for heterogeneous parallel architectures. In particular, we discuss the implementation for the multi-core IBM Cell Broadband Engine (Cell/B.E.) and provide extensive performance measurements and tradeoffs using two different scan orders or histogram propagation methods. For 640×480 images, a tile or block size of 28×28 and 16 histogram bins the parallel algorithm is able to reach greater than real-time performance of more than 200 frames per second.
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Bellens, P., Palaniappan, K., Badia, R.M., Seetharaman, G., Labarta, J. (2011). Parallel Implementation of the Integral Histogram. In: Blanc-Talon, J., Kleihorst, R., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2011. Lecture Notes in Computer Science, vol 6915. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23687-7_53
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DOI: https://doi.org/10.1007/978-3-642-23687-7_53
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