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An Image Enhancement Algorithm Based on Gaussian Mixture Model

A Gaussian mixture model and image enhancement technology, applied in the field of image processing, can solve the problems of brightness saturation, loss of details, amplification noise, etc.

Active Publication Date: 2016-10-19
CHANGCHUN INST OF OPTICS FINE MECHANICS & PHYSICS CHINESE ACAD OF SCI
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  • Claims
  • Application Information

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Problems solved by technology

Among them, histogram equalization is widely used in improving image contrast, but the current enhancement algorithm based on histogram equalization is prone to brightness saturation, loss of details or amplification of noise.

Method used

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  • An Image Enhancement Algorithm Based on Gaussian Mixture Model
  • An Image Enhancement Algorithm Based on Gaussian Mixture Model
  • An Image Enhancement Algorithm Based on Gaussian Mixture Model

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Embodiment Construction

[0030] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0031] The present invention is based on the image enhancement algorithm of Gaussian mixture model, and its steps are as follows:

[0032] First, the brightness components of the color image are counted into a histogram, and the Gaussian mixture modeling is performed on the histogram, that is, the Gaussian parameters are initialized. The Gaussian Mixture Model (Gaussian Mixture Modeling, GMM) is a linear mixture of Gaussian distributions with different parameters, and each Gaussian cluster corresponds to a set of mean, variance and weighting coefficients. Suppose X is the input image, and the data is histogram data h(x)={h(x 1 ), h(x 2 ),...,h(x N )}, the probability distribution of its gray level is p(x), then the histogram of the image can use GMM to construct the form of M Gaussian clustering linear mixture, namely

[0033] p ...

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Abstract

The invention relates to the technical field of image processing and provides an image enhancement algorithm based on a gauss hybrid model. According to the method, at first, luminance components of a color image are counted into a histogram, and mixture gauss modeling is carried out on the histogram; secondly, an improved EM algorithm is used for carrying out gauss hybrid model estimation on the histogram, a parameter of expectation maximization of a likelihood function is found out, and the optimum cluster quantity is determined through self-adaptation; thirdly, partition is carried out on the histogram according to an intersection point of adjacent clusters, and a plurality of sub-histograms are obtained; finally, the mapped clusters are found out according to the fact that area proportions of the sub-histograms with mapping relations are equal, the mapping function is adjusted in a micro mode according to application of the characteristic that the maximum entropy method tends to the human vision, and the final enhanced image is obtained. By the adoption of the image enhancement technology, the algorithm effectively improves the contrast ratio of the image, and increases the processing speed. The enhanced image obtained through the method achieves good effects in subjective visual perception aspect and objective evaluation aspect.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image enhancement algorithm based on a Gaussian mixture model. Background technique [0002] Image information is increasingly used by people to identify and judge things and solve practical problems. However, due to factors such as weather brightness and exposure conditions, the brightness of the image is dark or even blurred, which often cannot meet the needs of the application, which will seriously affect the recognition of the target. This type of image generally has the characteristics of relatively concentrated gray scale and low image contrast. Therefore, it is very important to improve the image contrast and perform post-processing on the image. Histogram correction technology has attracted attention because of its simplicity and ease of implementation. Among them, histogram equalization is widely used in improving image contrast, but the current enhancement...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06T5/40
Inventor 朱明陈莹
Owner CHANGCHUN INST OF OPTICS FINE MECHANICS & PHYSICS CHINESE ACAD OF SCI