5 research outputs found

    Recent Advances in Signal Processing

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    The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

    Spatio-Chromatic ICA of a Mosaiced Color Image

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    Abstract. We analyze whether Independant Component Analysis (ICA) is an appropriate tool for estimating spatial information in spatio-chromatic mosaiced color images. In previous studies, ICA analysis of natural color scenes (Hoyer et al. 2000; Tailor et al., 2000; Wachtler et al., 2001; Lee et al. 2002) have shown the emergence of achromatic patterns that can be used for luminance estimation. However, these analysis are based on fully defined spatio-chromatic images, i.e. three or more chromatic values per pixel. In case of a reduced spatio-chromatic set with a single chromatic measure per pixel, such as present in the retina or in CFA images, we found that ICA is not an appropriate tool for estimating spatial information. By extension, we discuss that the relationship between natural image statistics and the visual system does not remain valid if we take into account the spatio-chromatic sampling by cone photoreceptors.

    GEOBIA 2016 : Solutions and Synergies., 14-16 September 2016, University of Twente Faculty of Geo-Information and Earth Observation (ITC): open access e-book

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