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Self-adaptive enhancement algorithm of weighted histogram of infrared image

A technology of weighted histogram and adaptive enhancement, applied in image enhancement, image data processing, calculation, etc., can solve the problems of noise interference, loss of detail information, and difficult control of enhancement effect.

Inactive Publication Date: 2010-01-06
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0020] However, the histogram equalization algorithm is to enhance all the pixels of the entire image, and the specific enhancement effect is not easy to control, which often makes the details of some gray values ​​with similar gray levels and less distribution in the image lost, and cannot fully display the image. The goal
In addition, there is unexpected noise interference for global histogram equalization

Method used

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  • Self-adaptive enhancement algorithm of weighted histogram of infrared image
  • Self-adaptive enhancement algorithm of weighted histogram of infrared image
  • Self-adaptive enhancement algorithm of weighted histogram of infrared image

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Embodiment Construction

[0064] Below in conjunction with accompanying drawing and example the present invention is further described

[0065] image 3 It is an infrared image with a size of 266×400×3, from which we can see that the image contrast is very low and the edges and details are blurred. After the program reads the image, it will be converted to a size of 266×400 A grayscale image such as Figure 4 , whose histogram is as Image 6 , at this time we can find that the dynamic range of its gray value is not wide, and then use the Laplacian operator to calculate their frequency information for each point, the Laplacian mask template is as follows figure 2 shown; then after taking the modulo analysis of B(i, j), divide the whole image into target segment, background segment and interference segment; calculate T through steps 2, 3 and 4 1 , T 2 , and then through step 5 to obtain two kinds of frequency factors E(i, j), F(i, j), the former is to weight each point (the weight of each point in t...

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Abstract

The invention relates to a self-adaptive enhancement algorithm of a weighted histogram of an infrared image, which is a self-adaptive infrared image enhancement algorithm having the capacity of frequency characteristic processing of a space domain method. An image is divided into a target information section, a background information section and a noise information section by analyzing the grayscale information of each pixel of an original image so as to self-adaptively obtain two frequency factors. The first frequency factor E(i, j) is firstly utilized to weight a histogram of the original image by maintaining the frequency information of a part of pixels and modifying the frequency information of other parts of pixels to suppress noise and useless information and magnify target information; subsequently, threshold value processing is carried out on the weighted histogram through an automatic generating platform so as to obtain a new histogram; then equalization processing is carried; and finally, the other frequency factor F(i, j) is utilized to fine adjust the grayscales of each pixel. When the self-adaptive enhancement algorithm is used for carrying out infrared image processing, an infrared image with good enhancement effect can be guaranteed, and meanwhile, compared with a conventional frequency domain processing method, the self-adaptive enhancement algorithm improves the processing speed.

Description

technical field [0001] The invention belongs to the technical field of infrared image processing, and particularly relates to an infrared image enhancement algorithm for adaptive control of a weighted histogram, that is, an image enhancement method for performing adaptive control after weighting the histogram of an infrared grayscale image. Background technique [0002] Due to the sensitivity, resolution and other related characteristics of the imaging device, as well as the interference of various noises on the system, the infrared imaging system makes the infrared image have the characteristics of low contrast, low signal-to-noise ratio, high background, and blurred edges. In order to eliminate image noise, clarify image details and identify infrared image targets well, it is necessary to enhance the image. [0003] Image enhancement processing does not increase the inherent information of image data, but can expand the dynamic range of information. There are two main pur...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 汤海严高师杨昕梅漆强
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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