Fast Algorithm for Local Statistics Calculation for N -Dimensional Images |
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| Affiliation: | 1. Nursing and Midwifery Research Centre, Nursing and Midwifery Directorate, Northern Sydney Local Health District, St Leonards, NSW 2065, Australia;2. Faculty of Health, University of Technology Sydney, Ultimo, 2007 NSW, Australia;3. Emergency Department, Hornsby Hospital, Northern Sydney Local Health District, Palmerston Road, Hornsby, NSW 2077, Australia;4. NSLHD Libraries, Royal North Shore Hospital, Northern Sydney Local Health District, St Leonards, NSW 2065, Australia;1. School of Nursing and Health Sciences, The College of New Jersey, Ewing, NJ;2. School of Nursing, Widener University, Chester, PA;3. Department of Healthcare, Thomas Jefferson University Hospital, Philadelphia, PA;4. Department of Healthcare, Einstein Medical Center, Philadelphia, PA;5. Department of Healthcare, Cooper University Hospital, Camden, NJ;6. Department of Healthcare, The Hospital of the University of Pennsylvania, Philadelphia, PA;7. Department of Healthcare, Temple University Hospital, Philadelphia, PA;8. Department of Healthcare, Frontier Nursing University, Versailles, KY;1. Department of Radiology, University of Colorado Anschutz Medical Campus, 12700 E, 19th Avenue Mail Stop C278, Aurora, CO, 80045, USA;2. Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA;3. Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, 80309, USA;1. State Key Laboratory Breeding Base of Green Pesticide & Agricultural Bioengineering, Key Laboratory of Green Pesticide & Agricultural Bioengineering, Ministry of Education, State-Local Joint Engineering Lab for Comprehensive Utilization of Biomass, Center for R&D of Fine Chemicals, Guizhou University, Guiyang, China;2. Laboratory of Bioproduct Chemistry, Center of Innovative and Applied Bioprocessing (CIAB), Mohali, Punjab, India;1. Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Via Montpellier 1, 00133 Rome, Italy;2. National AIDS Center, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy;3. Laboratory of Immunoinfectivology, Bambino Gesù Children׳s Hospital, IRCCS, Piazza S. Onofrio 4, 00165 Rome, Italy |
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| Abstract: | Local mean and variance measures are frequently required in multi-dimensional image analysis. These measures are needed when calculating correlation coefficients for local image matching purposes. Other measures such as skewness and autocorrelation are useful for texture analysis. This paper presents a fast algorithm for calculating these local statistics in a window of an N -dimensional image. The new algorithm, which is called the plunger method, recursively reduces the dimensions of the input N -dimensional image to achieve fast computation. The speed of the algorithm is independent of the window size. Another advantage of the algorithm is that it calculates the local statistics in one pass. Real image tests have been performed. |
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