Multidimensional, digital signal processing
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This book introduces the theory and practical methods of multidimensional digital signal processing (MDSP), focusing on signals that depend on more than one variable, such as images and spatial data. It begins with the mathematical foundations, including multidimensional discrete-time signals and systems, convolution, and Fourier transforms in multiple dimensions. The authors then explore the design and analysis of multidimensional digital filters, emphasizing both separable and non-separable systems. A major part of the text is devoted to spectral analysis and transform techniques, which are essential for image processing and pattern recognition. The book also discusses system realization and computational structures for efficient implementation. Practical applications are highlighted, particularly in image enhancement, restoration, and data compression. Additionally, it addresses issues such as stability, causality, and implementation constraints in multidimensional systems.
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