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Kernel smoothing M.C. Jones, M.P. Wand
Publisher: Chapman & Hall

The basic idea is to find the modes of the image histogram which is processed by kernel smoothing [15]. Saturday, 20 April 2013 at 09:16. The kernel density estimator, j(x), is a nonparametric estimator of the probability density function of a data set and is defined by. The technique involves using what is called “kernel smoothing”. The kernel function generally peaks at the center and decay as it moves away from the center. Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-Plus Illustrations (Oxford Statistical Science Series) book download. This code takes image name and the kernel size as arguments and does Gaussian smoothing by creating a Gaussian kernel of specified size and apply the kernel to the image. Instead of using those methods and just choosing a bin size, I decided to smooth things out, and create an average histogram. It is basically a sort of smoothing. The output will be a blurred image.