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Image enhancement method based on image intensity threshold value and self-adaptive cutting

An image enhancement and image intensity technology, applied in image enhancement, image analysis, image data processing, etc., can solve the problems of not considering the image features of different regions, image detail loss, large noise and intensity saturation effect, so as to avoid image information Lost, prevents over-enhancement, avoids lost effects

Active Publication Date: 2020-02-28
CENT SOUTH UNIV
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Problems solved by technology

Although the traditional histogram equalization technology has many advantages, compared with the original image, the average brightness of the processed image will be greatly changed, and this method also introduces a large noise and intensity saturation effect, which leads to the loss of image details and unnatural image representation
This is because the traditional histogram equalization method does not consider the image characteristics of different regions, nor does it take into account the excessive enhancement of special regions, so the resulting images cannot meet the actual industrial environment

Method used

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  • Image enhancement method based on image intensity threshold value and self-adaptive cutting
  • Image enhancement method based on image intensity threshold value and self-adaptive cutting
  • Image enhancement method based on image intensity threshold value and self-adaptive cutting

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Embodiment Construction

[0050] The present invention will be further described below in conjunction with examples.

[0051] The image enhancement method based on the image intensity threshold and adaptive cutting provided by the present invention can preserve the information of the original image to the greatest extent, fully consider the detail information of the image, and reduce the noise level. like figure 1 As shown, the method includes the following steps:

[0052] Step 1: Calculate the image brightness threshold, and divide the original image histogram into a dark region histogram and a bright region histogram according to the image brightness threshold;

[0053] Among them, the calculation formula of the image brightness threshold is as follows:

[0054]

[0055] In the formula, T is the brightness threshold of the image, L is the gray level value of the image, which is 256; m represents the brightness at the pixel point (i, j) in the image, and p(m) represents the pixel point with brigh...

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Abstract

The invention discloses an image enhancement method based on an image intensity threshold value and self-adaptive cutting. The method comprises the following steps: dividing an original image histogram into a dark region histogram and a bright region histogram according to an image brightness threshold value; segmenting the dark region histogram and the bright region histogram into sub-histogramsof which the pixel points are equal in number respectively; calculating a median pixel number and a mean pixel number of each sub-histogram, and selecting an amplitude limiting threshold of each sub-histogram from the median pixel number and the mean pixel number; using the amplitude limiting threshold value of each sub-histogram for transversely cutting the corresponding sub-histogram to obtain anew sub-histogram; and performing equalization processing on each new sub-histogram to obtain a new image after image enhancement. According to the method, the image is enhanced, so that the enhancedimage not only has complete detail expression, but also is consistent with the content of the original image to the maximum extent.

Description

technical field [0001] The invention belongs to the field of image enhancement, in particular to an image enhancement method based on image intensity threshold and adaptive cutting. Background technique [0002] The purpose of image enhancement is to reveal hidden details in low-contrast images. Image enhancement has been widely used in medical images, face recognition and underwater images. The main idea of ​​histogram equalization is to flatten the probability distribution and remap the gray levels of the image, thus improving the image contrast. Histogram equalization is widely used for image contrast enhancement due to its simple function equation and effective enhancement properties. Although the traditional histogram equalization technology has many advantages, compared with the original image, the average brightness of the processed image will be greatly changed, and this method also introduces a large noise and intensity saturation effect, which leads to the loss o...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T5/40G06T7/11G06T7/136
CPCG06T5/40G06T7/11G06T7/136G06T2207/20004G06T2207/20132G06T5/90
Inventor 肖晓明朱湘源郭璠唐琎
Owner CENT SOUTH UNIV
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