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Revision with unchanged content. Visual sensor networks (VSN) that employ content-rich 2-D images or image sequences as the basic media have been evolving rapidly in recent years. Besi des the critical resource constraints that are already inherent in any wireless sensor networks, the development of VSNs also faces challenges from device design, image transmission, and onboard image processing, among which efficient onboard processing is the most difficult to tackle. The focus of this book is to develop efficient image processing solutions from three aspects: to improve the time-consuming image processing algorithms using pipelined and parallel computing; to distribute the computation more effectively through novel function and image partitioning, clustering, and mapping approaches; and to implement these techniques on the virtual micro-sensor platform for fast onboard image processing. Several new algorithms, models, and intellectual property (IP) are proposed for individual sections. The book is addressed to professionals like researchers and engineers in digital signal / image processing and parallel / distributed computing. It is also directed towards architects and designers in digital VLSI systems and portable devices.

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Ph.D. ECE at University of Tennessee. His research areas include parallel/distributed image and signal processing systems, digital VLSI, virtual platform, and high performance computing. He was listed on the Who s Who in America, Who s Who in Science and Engineering, and is the recipient of the Extraordinary Professional Promise Award.

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