A Shallow Sea Underwater Image Enhancement Method Based on Relative Global Histogram Stretching

Abstract

The invention relates to a shallow sea underwater image enhancement method based on relative global histogram extension. The shallow sea underwater image enhancement method comprises input image module, an image RGB histogram distribution analysis module, a relative global histogram extension module, a global extension module and an output image module. The advantages are that the method is low in image enhancement computation complexity, good in effect, good in robustness and suitable for various shallow sea underwater images of underwater plants, shallow sea personnel and seabed rocks and the like; the method can calculate parameters of a relative extension range and automatically select the extension range, and can accurately position a range to be extended; through a color correction method, color loss of global extension of S and V is carried out through an HSV color space; and the method can enhance contrast, saturation and visibility of each underwater image.

Description

technical field

[0001] The invention relates to the technical field of underwater image enhancement, in particular to a shallow sea underwater image enhancement method based on relative global histogram stretching. Background technique

[0002] In order to explore underwater fishery resources, mineral resources, and geological structures, people need to restore the real situation underwater through underwater images. However, underwater images have low visibility and low contrast. In recent years, more and more people are studying how to enhance underwater images, but the image enhancement technology that takes into account effectiveness, real-time and robustness is still facing challenges. Since underwater images are subject to light dispersion and absorption, the degradation of image quality is mainly reflected in the loss of image contrast saturation.

[0003] Restoring clear and real underwater images and videos is of great significance to the research of marine ecology...

Examples

Embodiment 1

[0054] refer to figure 1 , a shallow sea underwater image enhancement method based on relative global histogram stretching of the present invention, including analyzing the underwater image RGB histogram distribution module, relative global histogram stretching module, converting into HSV model and global stretching module, in,

[0055] Input the image module to obtain underwater images;

[0056] The image RGB histogram distribution analysis module splits the image into three channels and generates the corresponding histogram;

[0057] Compared with the global histogram stretching module, according to the histogram distribution characteristics of different channels, adaptively obtain the histogram stretching range;

[0058] The global stretching module performs color correction on the image, and then globally stretches the image;

[0059] The output image module will output the image after global stretching.

Embodiment 2

[0061] refer to figure 2 , the workflow of a shallow sea underwater image enhancement method based on relative global histogram stretching of the present invention is as follows:

[0062] S1: input image module

[0063] Acquire underwater images;

[0064] S2: Image RGB histogram distribution analysis module

[0065] S21: Split each image into three channels and generate corresponding histograms, namely red histogram, green histogram, and blue histogram;

[0066] S22: Analyze the distribution range of the histogram and obtain the corresponding distribution law. The red histogram is concentrated in [0,50], and the green and blue histograms are concentrated in [100,150];

[0067] S3: relative global histogram stretching module

[0068] S31: Calculating relevant parameters of the RGB channel, including average value, variance, and mean difference;

[0069] S311: Calculate the average value of the RGB channels, the calculation formula of which is shown in (1),

[0070]

...

Embodiment 3

[0093] A comparative experiment of a shallow sea underwater image enhancement method based on relative global histogram stretching of the present invention.

[0094] The method of the present invention is compared with ICM, UCM, and its histogram distribution result is as follows image 3 shown.

[0095] image 3 (a), (b), (c), and (d) are the histogram distribution diagrams of the original image, ICM processing, UCM processing, and the same image processed by the present invention, respectively.

[0096] It can be seen from the figure that the image processed by the present invention has a wider and more uniform color distribution, and is clearer and fuller in color than the original image and the image processed by ICM or UCM.

technical field

[0001] The invention relates to the technical field of underwater image enhancement, in particular to a shallow sea underwater image enhancement method based on relative global histogram stretching. Background technique

[0002] In order to explore underwater fishery resources, mineral resources, and geological structures, people need to restore the real situation underwater through underwater images. However, underwater images have low visibility and low contrast. In recent years, more and more people are studying how to enhance underwater images, but the image enhancement technology that takes into account effectiveness, real-time and robustness is still facing challenges. Since underwater images are subject to light dispersion and absorption, the degradation of image quality is mainly reflected in the loss of image contrast saturation.

[0003] Restoring clear and real underwater images and videos is of great significance to the research of marine ecology...

Examples

Embodiment 1

[0054] refer to figure 1 , a shallow sea underwater image enhancement method based on relative global histogram stretching of the present invention, including analyzing the underwater image RGB histogram distribution module, relative global histogram stretching module, converting into HSV model and global stretching module, in,

[0055] Input the image module to obtain underwater images;

[0056] The image RGB histogram distribution analysis module splits the image into three channels and generates the corresponding histogram;

[0057] Compared with the global histogram stretching module, according to the histogram distribution characteristics of different channels, adaptively obtain the histogram stretching range;

[0058] The global stretching module performs color correction on the image, and then globally stretches the image;

[0059] The output image module will output the image after global stretching.

Embodiment 2

[0061] refer to figure 2 , the workflow of a shallow sea underwater image enhancement method based on relative global histogram stretching of the present invention is as follows:

[0062] S1: input image module

[0063] Acquire underwater images;

[0064] S2: Image RGB histogram distribution analysis module

[0065] S21: Split each image into three channels and generate corresponding histograms, namely red histogram, green histogram, and blue histogram;

[0066] S22: Analyze the distribution range of the histogram and obtain the corresponding distribution law. The red histogram is concentrated in [0,50], and the green and blue histograms are concentrated in [100,150];

[0067] S3: relative global histogram stretching module

[0068] S31: Calculating relevant parameters of the RGB channel, including average value, variance, and mean difference;

[0069] S311: Calculate the average value of the RGB channels, the calculation formula of which is shown in (1),

[0070]

...

Embodiment 3

[0093] A comparative experiment of a shallow sea underwater image enhancement method based on relative global histogram stretching of the present invention.

[0094] The method of the present invention is compared with ICM, UCM, and its histogram distribution result is as follows image 3 shown.

[0095] image 3 (a), (b), (c), and (d) are the histogram distribution diagrams of the original image, ICM processing, UCM processing, and the same image processed by the present invention, respectively.

[0096] It can be seen from the figure that the image processed by the present invention has a wider and more uniform color distribution, and is clearer and fuller in color than the original image and the image processed by ICM or UCM.

Images