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An Image Enhancement Method Based on Image Intensity Threshold and 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 characteristics of different regions, unnatural image performance, image detail loss, etc., to avoid image information loss, The effect of fast calculation speed and simple operation

Active Publication Date: 2022-05-10
CENT SOUTH UNIV
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  • Summary
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  • Application Information

AI Technical Summary

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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  • An Image Enhancement Method Based on Image Intensity Threshold and Adaptive Cutting
  • An Image Enhancement Method Based on Image Intensity Threshold and Adaptive Cutting
  • An Image Enhancement Method Based on Image Intensity Threshold and 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 image intensity threshold and adaptive cutting, comprising: dividing the original image histogram into a dark area histogram and a bright area histogram according to the image brightness threshold; dividing the dark area histogram and the bright area histogram The histogram is divided into sub-histograms with the same number of pixels; the median pixel number and mean pixel number of each sub-histogram are calculated, and the clipping of each sub-histogram is selected from the median pixel number and mean pixel number Threshold; use the clipping threshold of each sub-histogram to horizontally cut the corresponding sub-histograms to obtain new sub-histograms; respectively perform equalization processing on each new sub-histogram to obtain a new image after image enhancement. The present invention enhances the image through the method so that the enhanced image not only has complete details, but also must be consistent with the content of the original image to the greatest 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 Patents(China)
IPC IPC(8): G06T5/00G06T5/40G06T7/11G06T7/136
CPCG06T5/007G06T5/40G06T7/11G06T7/136G06T2207/20004G06T2207/20132
Inventor 肖晓明朱湘源郭璠唐琎
Owner CENT SOUTH UNIV
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