Springer, 2010. — 182 p.The ‘Fuzzy Logic’ research group of the Microelectronics Institute of Seville is composed of researchers who have been doing research on fuzzy logic since the beginning of the 1990s. Mainly, this research has been focused on the microelectronic design of fuzzy logic-based systems using implementation techniques which range from ASICs to FPGAs and DSPs. Another active line was the development of a CAD environment, named Xfuzzy, to ease such design. Several versions of Xfuzzy have been and are being currently developed by the group. The addressed applications had basically belonged to the control field domain. In this sense, several problems without a linear control solution had been studied thoroughly. Some examples are the navigation control of an autonomous mobile robot and the level control of a dosage system. The research group tackles a new activity with the work developed in this book: the application of fuzzy logic to video and image processing. We addressed our interest to problems related to pixel interpolation, with the aim of adapting such interpolation to the local features of the images. Our hypothesis was that measures and decisions to solve image interpolation, which traditionally had been done in a crisp way, could better be done in a fuzzy way. Validation of this general hypothesis has been done specifically in the interpolation problem of video de-interlacing. Deinterlacing is one of the main tasks in video processing. It is necessary whenever the transmission standard uses an interlaced format but the receiver requires a progressive scanning, as happens to LCDs and plasma displays, projectors, and DVDs. Besides, de-interlacing is usually the first step before applying conversion between two formats, a practice in crescent use due to the proliferation of different video formats.Basic Concepts Fuzzy Motion-Adaptive Algorithm for Video De-Interlacing Design Options of the Fuzzy Motion-Adaptive Algorithm Fuzzy Motion-Adaptive De-Interlacing with Edge-Adaptive Spatial Interpolation Fuzzy Motion-Adaptive De-Interlacing with Smart Temporal Interpolation
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