gaussian | 易学教程

Is there any Difference of Gaussians function in Matlab?

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I am new to Image Processing, and in my experiment I am having difficulty with Difference of Gaussians. Various implementation were given to me but I don't understand them and their parameters. Here are my formulas Should I implement this filtering myself, or is there an existing function defined for this? Of course with all parameters which are like in link. I will need to play with parameters and produce different images. You could Gaussian filter an image twice with two different std. dev. and just subtract them, would be the same as using the combined filter. k = 10; sigma1 = 0.5; sigma2 =

Gaussian Mixture Models of an Image's Histogram

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I am attempting to do automatic image segmentation of the different regions of a 2D MR image based on pixel intensity values. The first step is implementing a Gaussian Mixture Model on the image's histogram. I need to plot the resulting gaussian obtained from the score_samples method onto the histogram. I have tried following the code in the answer to ( Understanding Gaussian Mixture Models ). However, the resulting gaussian fails to match the histogram at all. How do I get the gaussian to match the histogram? import numpy as np import cv2 import matplotlib.pyplot as plt from sklearn.mixture

multivariate normal cdf in C, C++, or Fortran [closed]

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Is there an open source to calculate multivariate (where dimension is large > 3, not bivariate or trivariate ) numerical cdf of gaussian distributions in C, C++ or Fortran? I believe IMSL does it; http://www.roguewave.com/portals/0/products/imsl-numerical-libraries/c-library/docs/7.0/html/cstat/default.htm?turl=multivariatenormalcdf.htm Andrew Mao You should go to the source...this dude Professor Alan Genz has been researching how to do this and other multivariate integrals numerically since the 1980's. All of the code that others have implemented are derived from his algorithm and papers. His

gaussian blur with FFT

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im trying to implement a gaussian blur with the use of FFT and could find here the following recipe. This means that you can take the Fourier transform of the image and the filter, multiply the (complex) results, and then take the inverse Fourier transform. I've got a kernel K, a 7x7 Matrix and a Image I, a 512x512 Matrix. I do not understand how to multiply K by I. Is the only way to do that by making K as big as I (512x512) ? Yes, you do need to make K as big as I by padding it with zeros. Also, after padding, but before you take the FFT of the kernel, you need to translate it with

Gaussian filter in MATLAB

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问题 Does the 'gaussian' filter in MATLAB convolve the image with the Gaussian kernel? Also, how do you choose the parameters hsize (size of filter) and sigma? What do you base it on? 回答1: You first create the filter with fspecial and then convolve the image with the filter using imfilter (which works on multidimensional images as in the example). You specify sigma and hsize in fspecial . Code: %%# Read an image I = imread('peppers.png'); %# Create the gaussian filter with hsize = [5 5] and sigma

Gaussian Filter on a vector in Matlab [duplicate]

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This question already has an answer here: one Dimensional gauss convolution function in Matlab 2 answers I have a n-dimensional vector (1xn dataset, and it is not image data), and I want to apply a Gaussian filter to it. I have the Image Processing Toolkit, and a few others (ask if you need a list). Presumably I can make the hsize parameter of the fspecial function something like [1 n] . Can I still use imfilter to apply it to my vector as the next step, or should I be using something else? I've seen quite a few examples on how to apply a Gaussian filter to two dimensional image data in Matlab

Fit data to normal distribution

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问题 I want some data to fit the corresponding Gaussian distribution. The data is meant to be Gaussian already, but for some filtering reasons, they will not perfectly match the prescribed and expected Gaussian distribution. I therefore aim to reduce the existing scatter between data and desired distribution. For example, my data fit the Gaussian distribution as follows (the expected mean value is 0 and the standard deviation 0.8): The approximation is already decent, but I really want to crunch

Random Numbers with Gaussian and Uniform Distributions in matlab

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问题 I want generate a number in Gaussian and Uniform distributions in matlab. I know this function randi and rand() but all of them are in normal (Gaussian) distribution. How can a generate a random number in uniform distribution? 回答1: Use rand(dimensions) for a Uniform Distribution between 0 and 1. Use randn(dimensions) * sqrt(sigma) + mu for a Gaussian Distribution with a mean of mu and variance of sigma . 回答2: randn is the function to generate Gaussian distributed variables ( randi and rand

How to specify upper and lower limits when using numpy.random.normal

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问题 IOK so I want to be able to pick values from a normal distribution that only ever fall between 0 and 1. In some cases I want to be able to basically just return a completely random distribution, and in other cases I want to return values that fall in the shape of a gaussian. At the moment I am using the following function: def blockedgauss(mu,sigma): while True: numb = random.gauss(mu,sigma) if (numb > 0 and numb < 1): break return numb It picks a value from a normal distribution, then

Display images in different sizes in MATLAB

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问题 I am creating gaussian pyramid in MATLAB 2010b. I want to show images like same patterned mentioned here. I tried to use imresize , truesize but getting all images in same size. Could anybody please help me on this issue? 回答1: You can use "imshow with True Size for multiple images" FEX file to answer your question... EDIT : The code below will produce the subplot at the bottom right part of the figure: clear imagesCellArray mand = imread('mandelbrot_set.jpg'); % read image dim = 3;