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Digital signal transforms are of a fundamental value in digital signal and image processing. Their role is manifold. Transforms selected appropriately enable substantial compressing signals and images for storage and transmission. No signal recovery, image reconstruction and restoration task can be efficiently solved without using digital signal transforms. Transforms are successfully used for logic design and digital data encryption. Fast transforms are the main tools for acceleration of computations in digital signal and image processing.
The volume collects in one book most recent developments in the theory and practice of the design and usage of transforms in digital signal and image processing. It emerged from the series of reports published by Tampere International Centre for Signal Processing, Tampere University of Technology. For the volume, all contributions are appropriately updated to represent the state of the art in the field and to cover the most recent developments in different aspects of the theory and applications of transforms.
The book consists of two parts that represent two major directions in the field: development of new transforms and development of transform based signal and image processing algorithms. The first part contains four chapters devoted to recent advances in transforms for image compression and switching and logic design and to new fast transforms for digital holography and tomography. In the second part, advanced transform based signal and image algorithms are considered: signal and image local adaptive restoration methods and two complementing families of signal and image re-sampling algorithms, fast transform based discrete sinc-interpolation and spline theory based ones.
Topics and Features: Benefits for Potential Reader:
Graduate and PhD students will find in one book most recent developments in the theory and practice of the design and usage of transforms in digital signal and image processing.
Educators in electrical engineering and computer science can use the book to enrich their courses.
Practical processing algorithms described in the book can be directly used by engineers, PhD and graduate students in their research.
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Jaakko Astola (Fellow of IEEE) received the Ph.D. degree in mathematics from Turku University, Finland, in 1978. From 1976 to 1977, he was with the Research Institute for Mathematical Sciences, Kyoto University, Kyoto, Japan. Between 1979 and 1987, he was with the Department of Information Technology, Lappeenranta University of Technology, Lappeenranta, Finland. In 1984, he worked as a Visiting Scientist in Eindhoven University of Technology, The Netherlands. From 1987 to 1992, he was an Associate Professor in Applied Mathematics at Tampere University, Tampere, Finland. From 1993, he has been a Professor of Signal Processing and Director of Tampere International Center for Signal Processing leading a group of about 60 scientists and was nominated as Academy Professor by Academy of Finland (2001 2006). His research interests include signal processing, coding theory, and spectral techniques and statistics.
Leonid P. Yaroslavsky is a Professor at the Department of Interdisciplinary Studies, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv University, Israel. His research interests are multidimensional and multi component digital image processing and data fusion, target location and tracking in clutter, optical and hybrid electro-optical correlators for target location, global and running window fast transforms and their applications, non-linear filters, 2-D neuro-morphic networks and 2-D deterministic chaos and digital holography.
His current and recent projects are target location in clutter, multi component image restoration, enhancement, segmentation, stabilization, fusion and super-resolution of turbulent visible range and thermal video sequences for terrestrial long distance observation systems, discrete sinc-interpolation and its applications in image and signal processing. In addition to fast transforms for digital holography, FPGA implementation of rank filters for image processing, 3-D stereoscopic visualization and 2D to 3D video conversion.
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