A Low-Illumination Image Enhancement Method Based on Local Contrast Stretching

A local contrast and image enhancement technology, which is applied in image enhancement, image data processing, instruments, etc., can solve the problems that the image details, texture and clarity of the enhanced image cannot be guaranteed, and the quality of the enhanced image is poor, so as to achieve enhanced brightness contrast and improved The effect of image quality

Active Publication Date: 2021-04-23
HARBIN UNIV OF SCI & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] The purpose of the present invention is to solve the problem that the image detail, texture and clarity of the enhanced image cannot be guaranteed by the existing method, resulting in the poor quality of the obtained enhanced image, and a low-illuminance image enhancement based on local contrast stretching is proposed method

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  • A Low-Illumination Image Enhancement Method Based on Local Contrast Stretching
  • A Low-Illumination Image Enhancement Method Based on Local Contrast Stretching
  • A Low-Illumination Image Enhancement Method Based on Local Contrast Stretching

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specific Embodiment approach 1

[0019] Specific implementation mode one: combine figure 1 This embodiment will be described. A low-illuminance image enhancement method based on local contrast stretching described in this embodiment, the method is specifically implemented through the following steps:

[0020] Step 1, collect the original RGB image, convert the collected original RGB image into an HSV image, and obtain the V channel data, H channel data and S channel data of the HSV image;

[0021] Step 2, performing local contrast stretching on the local contrast of the V channel data of the HSV image to obtain the stretched local contrast;

[0022] Step 3, performing grayscale mapping on the V channel data of the HSV image to obtain an initial iteration value;

[0023] Step 4, use the stretched local contrast and iterative initial value to calculate the enhanced V channel data, convert the HSV image formed by the H channel data, the S channel data and the enhanced V channel data into an RGB image, and obta...

specific Embodiment approach 2

[0024] Specific implementation mode two: combination figure 2 This embodiment will be described. The difference between this embodiment and the specific embodiment one is: the specific process of the second step is:

[0025] The form of the local contrast stretching function is shown in formula (1):

[0026]

[0027] in: Represents the stretched local contrast of the V channel pixel (x, y), C x,y Indicates the local contrast of the pixel point (x, y) in the V channel data obtained in step 1; A(0.45), B(0.45), A(1) and B(1) are intermediate functions.

specific Embodiment approach 3

[0028] Specific embodiment three: the difference between this embodiment and specific embodiment two is: the expressions of the intermediate functions A (0.45), B (0.45), A (1) and B (1) are respectively:

[0029] A(0.45)=max[(C x,y +1) 0.45 ] (2)

[0030] B(0.45)=min[(C x,y +1) 0.45 ] (3)

[0031] A(1)=max(C x,y +1) (4)

[0032] B(1)=min(C x,y +1) (5)

[0033] Among them: max means to take the maximum value, and min means to take the minimum value.

[0034] In this embodiment, in the process of obtaining the maximum and minimum values, it is necessary to traverse the local contrast of each pixel in order to obtain (C x,y +1) 0.45 The maximum and minimum values ​​of (C x,y +1) maximum and minimum values.

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Abstract

A low-illuminance image enhancement method based on local contrast stretching belongs to the technical field of image enhancement. The invention solves the problem that the image detail, texture and clarity of the enhanced image cannot be guaranteed by the existing method, resulting in poor quality of the obtained enhanced image. The present invention firstly stretches the local contrast of the image, so as to improve the texture, detail and clarity of the output image. Secondly, a segmented global grayscale mapping method is designed to calculate the initial value of the iterative process, so as to improve the global brightness contrast of the enhanced image. Experimental results verify that the image enhancement algorithm designed in the present invention can effectively improve the image quality, enhance the brightness contrast of the image, and the image details are very suitable for human observation. The invention can be applied to the enhancement of low-illuminance images.

Description

technical field [0001] The invention belongs to the technical field of image enhancement, and in particular relates to a low-illuminance image enhancement method based on local contrast stretching. Background technique [0002] Due to the uneven illumination of the real environment, there are low-illumination areas in digital images with low brightness. The presence of low-illuminance areas leads to poor image visibility, and it is difficult to recognize details, textures, and image content in low-illuminance areas. Therefore, how to overcome the problem of image quality degradation caused by low-illumination areas has become a hot spot in academic research. Commonly used low-light image enhancement algorithms include: contrast enhancement algorithm based on histogram equalization; image enhancement algorithm based on global gray scale stretching; image enhancement algorithm based on wavelet transform, etc. Although these algorithms can improve the light-dark contrast of t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06T5/40
CPCG06T5/007G06T5/40
Inventor 赵蓝飞孙瑞阳段炼孙玉滨
Owner HARBIN UNIV OF SCI & TECH
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