Histogram Approximation Based on Expectation Maximization Algorithm and Its Application
基于EM的直方图逼近及其应用

Histogram is commonly the statistical information about gray level or other chromatic components of image.Analyzing the histogram of image is a useful method in image processing.Adopting several probability density functions(PDFs) with Gaussian distribution to approximate the histogram is one way for histogram analyzing.But how to acquire the parameters of these distributions remains a hard issue.This paper uses expectation maximization algorithm to estimate the parameters by converting histogram apporximation problem into Guassian mixture models problem in statistics,and then introduces its application in optimal thresholding and histogram component analysis.