Fuzzy Integral Filters: Properties and Parallel Implementation |
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| Affiliation: | 1. Mechatronics Group, Singapore Institute of Manufacturing Technology, Singapore 638075, Singapore;2. School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore;3. Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Zhejiang Province 315201, China;1. College of New Energy, China University of Petroleum (East China), Qingdao 266580, PR China;2. The 711 Research Institute of CSIC, Shanghai 201108, PR China;3. College of Pipeline and Civil Engineering, China University of Petroleum (East China), Qingdao 266580, PR China;4. Shandong Key Laboratory of Oil & Gas Storage and Transport Safety, Qingdao 266580, PR China;5. Qingdao Engineering Research Center of Efficient and Clean Utilization of Fossil Energy, Qingdao 266580, PR China;1. CMT-Motores Térmicos, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain;2. Argonne National Laboratory, Energy Systems Division, Argonne, IL 60439, USA;3. Argonne National Laboratory, Advanced Photon Source, X-ray Science Division, Argonne, IL 60439, USA;1. CMT – Motores Térmicos, Universitat Politècnica de València, Edificio 6D, 46022 Valencia, Spain;2. Universidad de Castilla la Mancha, Departamento de Mecánica Aplicada e Ingeniería de Proyectos, Plaza Manuel Meca 1, 13400 Almadén, Spain |
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| Abstract: | Fuzzy integrals as image filters provide a standard representational form which generalize linear filters such as the averaging filter, morphological filters such as flat dilations and erosions, and order statistic filters such as the median filter. However, fuzzy integral filters are computationally intensive. Computing the output value obtained by fuzzy integral filtering at a point involves sorting all the pixels in a neighborhood of the point according to their values and then computing ordered weighted sum or maximum with respect to an appropriate fuzzy measure. In this paper we discuss some properties of fuzzy integral filters and describe a method for enhancing the processing elements of single instruction, multiple data (SIMD) mesh computers with comparators and counters to efficiently implement fuzzy integral filters. |
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