Computer Vision, Graphics, and Image Processing
Low level parallel image processing
Parallel algorithms
Brook for GPUs: stream computing on graphics hardware
ACM SIGGRAPH 2004 Papers
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Fast median and bilateral filtering
ACM SIGGRAPH 2006 Papers
Cell broadband engine architecture and its first implementation: a performance view
IBM Journal of Research and Development
Larrabee: a many-core x86 architecture for visual computing
ACM SIGGRAPH 2008 papers
Cell-SWat: modeling and scheduling wavefront computations on the cell broadband engine
Proceedings of the 5th conference on Computing frontiers
A Parallel Algorithm for Advanced Video Motion Estimation on Multicore Architectures
CISIS '08 Proceedings of the 2008 International Conference on Complex, Intelligent and Software Intensive Systems
Amdahl's Law in the Multicore Era
Computer
DMA Performance Analysis and Multi-core Memory Optimization for SWIM Benchmark on the Cell Processor
ISPA '08 Proceedings of the 2008 IEEE International Symposium on Parallel and Distributed Processing with Applications
Modeling multigrain parallelism on heterogeneous multi-core processors: a case study of the cell BE
HiPEAC'08 Proceedings of the 3rd international conference on High performance embedded architectures and compilers
Rate-constrained coder control and comparison of video coding standards
IEEE Transactions on Circuits and Systems for Video Technology
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Local processing, which is a dominant type of processing in image and video applications, requires a huge computational power to be performed in real-time. However, processing locality, in space and/or in time, allows to exploit data parallelism and data reusing. Although it is possible to exploit these properties to achieve high performance image and video processing in multi-core processors, it is necessary to develop suitable models and parallel algorithms, in particular for non-shared memory architectures. This paper proposes an efficient and simple model for local image and video processing on non-shared memory multi-core architectures. This model adopts a single program multiple data approach, where data is distributed, processed and reused in an optimal way, regarding the data size, the number of cores and the local memory capacity. The model was experimentally evaluated by developing video local processing algorithms and programming the Cell Broadband Engine multi-core processor, namely for advanced video motion estimation and in-loop deblocking filtering. Furthermore, based on these experiences it is also addressed the main challenges of vectorization, and the reduction of branch mispredictions and computational load imbalances. The limits and advantages of the regular and adaptive algorithms are also discussed. Experimental results show the adequacy of the proposed model to perform local video processing, and that real-time is achieved even to process the most demanding parts of advanced video coding. Full-pixel motion estimation is performed over high resolution video (720脳576 pixels) at a rate of 30 frames per second, by considering large search areas and five reference frames.