Parallel implementation of the integral histogram

Authors:
Pieter Bellens;Kannappan Palaniappan;Rosa M. Badia;Guna Seetharaman;Jesus Labarta
Affiliations:
Barcelona Supercomputing Center, Spain;Dept. of Computer Science, University of Missouri, Columbia, Missouri;Barcelona Supercomputing Center, Spain and Intelligence Research Institute (IIIA), Spanish National Research Council (CSIC), Spain;Air Force Research Laboratory, Information Directorate, Rome, New York;Barcelona Supercomputing Center, Spain and Universitat Politecnica de Catalunya, Spain
Venue:
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Year:
2011

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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.