Image Histogram Equalization Based on Gaussian Mixture Model
نویسندگان
چکیده
منابع مشابه
Image Segmentation using Gaussian Mixture Model
Abstract: Stochastic models such as mixture models, graphical models, Markov random fields and hidden Markov models have key role in probabilistic data analysis. In this paper, we used Gaussian mixture model to the pixels of an image. The parameters of the model were estimated by EM-algorithm. In addition pixel labeling corresponded to each pixel of true image was made by Bayes rule. In fact,...
متن کاملIMAGE SEGMENTATION USING GAUSSIAN MIXTURE MODEL
Stochastic models such as mixture models, graphical models, Markov random fields and hidden Markov models have key role in probabilistic data analysis. In this paper, we have learned Gaussian mixture model to the pixels of an image. The parameters of the model have estimated by EM-algorithm. In addition pixel labeling corresponded to each pixel of true image is made by Bayes rule. In fact, ...
متن کاملComparison of Automatic Image Contrast Enhancement Using Gaussian Mixture Model and Global Histogram Equalization
In this project, we have implemented Image Contrast Enhancement algorithm that automatically enhances the contrast in an input image. The algorithm uses the Gaussian mixture model to model the image gray-level distribution and the intersection points of the Gaussian components in the model are used to partition the dynamic range of the image into input gray-level intervals. The contrast equaliz...
متن کاملColour Image Enhancement Based on Histogram Equalization
Histogram equalization is a nonlinear technique for adjusting the contrast of an image using its histogram. It increases the brightness of a gray scale image which is different from the mean brightness of the original image. There are various types of Histogram equalization techniques like Histogram Equalization, Contrast Limited Adaptive Histogram Equalization, Brightness Preserving Bi Histogr...
متن کاملUnsupervised Color Image Segmentation Based on Gaussian Mixture Model
A novel color image segmentation method based on finite Gaussian mixture model is proposed in this paper. First, we use EM algorithm to estimate the distribution of input image data and the number of mixture components is automatically determined by MML criterion. Then the segmentation is carried out by clustering each pixel into appropriate component according to maximum likelihood (ML) criter...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Korea Multimedia Society
سال: 2012
ISSN: 1229-7771
DOI: 10.9717/kmms.2012.15.6.748