Signal Processing and Image Processing for Acoustical Imaging (eBook)

This book discusses the applications of signal and image processing in acoustical imaging. It first describes the basic tools involved - the 2D transform, fast Fourier transform (FFT) and applications, and deconvolution - before introducing readers to higher-order statistics, wavelets, and neural networks. It also addresses the important topic of digital signal processing, focusing on the example of homomorphic signal processing. The book then details the design of digital filters and array signal processing, and lastly examines applications in image processing: image enhancement and optimization, image restoration, and image compression.

Dr. Woon Siong Gan completed his B.Sc. in Physics in 1965, his DIC in Acoustics & Vibration Science in May 1967, and his Ph.D. in Acoustics in February 1969, all at the Physics Department of Imperial College London. He served as an Associate Professor at the Physics Department of Nanyang University, Singapore, from 1970 to 1979, and from 1979 to 1989, he was a practicing acoustical consultant. In 1989, he founded Acoustical Technologies Singapore Pte Ltd, a research & technologies company focusing on ultrasound technologies, especially acoustical imaging. The company has since developed and patented the scanning acoustic microscope (SAM) and the surface acoustic wave (SAW) device. He is also the author of the book: Acoustical Imaging: Techniques and Applications for Engineers, published by John Wiley & Sons in June 2012. He was the first to introduce transport theory into condensed matter physics in 1966 - transport theory is today the foundation of the theoretical design of materials. He also introduced symmetry properties into the acoustics field in 2007.

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This book discusses the applications of signal and image processing in acoustical imaging. It first describes the basic tools involved - the 2D transform, fast Fourier transform (FFT) and applications, and deconvolution - before introducing readers to higher-order statistics, wavelets, and neural networks. It also addresses the important topic of digital signal processing, focusing on the example of homomorphic signal processing. The book then details the design of digital filters and array signal processing, and lastly examines applications in image processing: image enhancement and optimization, image restoration, and image compression.