CN115082361A - Turbid water body image enhancement method based on image processing - Google Patents
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- 238000002834 transmittance Methods 0.000 claims description 40
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Abstract
The invention relates to the technical field of image enhancement, in particular to a turbid water body image enhancement method based on image processing, which comprises the following steps: the method comprises the steps of obtaining a turbid water body image, obtaining the fuzzy degree of each pixel point in the image, clustering the pixel points according to the fuzzy degree to obtain a plurality of cluster areas, obtaining the characteristic point of each cluster area, calculating the high light intensity value of the characteristic point, obtaining the transmissivity of the characteristic point, calculating the transmissivity of each pixel point in each cluster area corresponding to the characteristic point according to the transmissivity of the characteristic point, obtaining the reflected light intensity value of the pixel point in each cluster area according to the atmospheric light intensity value of each cluster area and the transmissivity of each pixel point in each cluster area, and obtaining the enhanced image of the turbid water body image according to the reflected light intensity values of all the pixel points and the atmospheric light intensity value of the turbid water body image.
Description
Technical Field
The invention relates to the technical field of image enhancement, in particular to a turbid water body image enhancement method based on image processing.
Background
When underwater resource detection or target identification is carried out, the transmissivity of light in a water body image is influenced due to the complex underwater environment and the activities of floating objects and underwater organisms in the water body, so that the image is blurred or shielded, and the image quality is poor due to image blurring.
When an image of a turbid water body is enhanced, in the prior art, image enhancement is mainly performed by using a dark channel prior defogging algorithm, wherein the dark channel prior defogging algorithm is to calculate a reflected light intensity value in the image according to the transmittance of the whole image and then obtain an image-enhanced pixel value according to the reflected light intensity value and an atmospheric light intensity value of the image.
However, when local regions with different degrees of turbidity exist in the turbid water body image, dark channels corresponding to the local regions with different degrees of turbidity are different, that is, the reflected light intensity values of the objects in the local regions with different degrees of turbidity are different, and the reflected light intensity values in the turbid water body image are affected by the transmittance, so that the reflected light intensity values of the objects in the local regions with different degrees of turbidity can not be accurately reflected by calculating the reflected light intensity values of the objects in the local regions with different degrees of turbidity by using the transmittance of the whole image, and the enhancement effect of the local regions in the enhanced image obtained by using the transmittance of the whole image is not good.
Therefore, it is desirable to provide an image enhancement method for a turbid water body based on image processing to solve the above problems.
Disclosure of Invention
The invention provides an image enhancement method for a turbid water body based on image processing, which aims to solve the existing problems.
The invention relates to a turbid water body image enhancement method based on image processing, which adopts the following technical scheme: the method comprises the following steps:
obtaining a turbid water body image;
acquiring a pixel difference value of each pixel point and a neighborhood pixel point in the turbid water body image, and taking the maximum pixel difference value as the fuzzy degree of the corresponding pixel point;
clustering the pixel points according to the fuzzy degree difference of each pixel point and the neighborhood pixel points to obtain a plurality of cluster areas;
taking a pixel point corresponding to the maximum fuzzy degree in the fuzzy degrees corresponding to all pixel points in each cluster region as a characteristic point of the corresponding cluster region;
acquiring a local dark channel map corresponding to each cluster area, acquiring an atmospheric light intensity value corresponding to each cluster area according to the local dark channel map, and taking the atmospheric light intensity value as an atmospheric light intensity value of a characteristic point of the cluster area;
obtaining the transmissivity corresponding to the characteristic points according to the atmospheric light intensity values of the characteristic points, and calculating the transmissivity of each pixel point in the corresponding cluster area according to the transmissivity corresponding to the characteristic points of each cluster area and the fuzzy degree of each pixel point;
and obtaining a reflected light intensity value of each pixel point of each clustering region in the turbid water body image according to the atmospheric light intensity value of each clustering region and the transmissivity of each pixel point in the clustering region, and obtaining an enhanced image of the turbid water body image according to the reflected light intensity values of all the pixel points and the atmospheric light intensity value of the turbid water body image.
Preferably, the turbid water body image is an image obtained by denoising the turbid water body image by using bilateral filtering.
Preferably, the step of clustering the pixel points according to the fuzzy degree difference of each pixel point and the neighboring pixel points thereof to obtain a plurality of clustering areas comprises:
setting a fuzzy degree difference threshold value;
and clustering the pixels of which the fuzzy degree difference value between each pixel and each neighborhood pixel is smaller than the fuzzy degree difference value threshold and the neighborhood pixels to obtain a plurality of cluster regions.
Preferably, the method further comprises the following steps:
setting an area threshold of a cluster region;
acquiring a target clustering region with the area smaller than an area threshold;
acquiring the mean value of first fuzzy degree difference values of all pixel points of a target clustering region and the mean value of second fuzzy degree difference values of all pixel points of each clustering region in the neighborhood of the target clustering region;
the mean value of the first fuzzy degree difference value and the mean value of each second fuzzy degree difference value are differentiated to obtain a mean value difference value;
dividing the target clustering region into clustering regions corresponding to the minimum mean difference value to obtain final clustering regions;
and taking the final cluster area as a cluster area.
Preferably, the step of acquiring the local dark channel map corresponding to each cluster region includes:
setting a window in a cluster area corresponding to each characteristic point by taking each characteristic point as a center;
acquiring the minimum value of all pixel points in the window in an RGB three channel;
and acquiring a local dark channel image corresponding to each window, and taking the local dark channel image as a local dark channel image corresponding to the cluster area.
Preferably, the step of obtaining the atmospheric light intensity value corresponding to each cluster region according to the local dark channel map includes:
taking pixel points which are less than 0.1% of the brightest value in the local dark channel image as target pixel points;
and taking the maximum brightness value of the target pixel point in the turbid water body image as the atmospheric luminous intensity value of the cluster region.
Preferably, the step of calculating the transmittance of each pixel point in the corresponding cluster region according to the transmittance corresponding to the feature point of each cluster region and the blurring degree of each pixel point comprises:
calculating the ratio of the fuzzy degree of the characteristic points of the cluster region to the fuzzy degree of the pixel points in the cluster region;
and taking the product of the ratio of the fuzzy degree of the characteristic points of the cluster region to the fuzzy degree of the pixel points in the cluster region and the transmissivity corresponding to the characteristic points as the transmissivity of the pixel points.
Preferably, the step of obtaining the enhanced image of the turbid water body image according to the reflected light intensity values of all the pixel points and the atmospheric light intensity value of the turbid water body image includes:
taking the sum of the reflected light intensity value of each pixel point and the atmospheric light intensity value of the turbid water body image as the pixel value of the pixel point after enhancement;
and obtaining an enhanced image of the turbid water body image according to the enhanced pixel values of all the pixel points.
The invention has the beneficial effects that: the invention relates to a turbid water body image enhancement method based on image processing, which is characterized in that pixel points are clustered by the aid of fuzziness of the pixel points to obtain a plurality of clustering regions, local regions with different turbidity degrees of a turbid water body image are divided, then characteristic points representing the turbidity degree of each clustering region are obtained, the transmissivity of each pixel point in each clustering region is obtained according to the transmissivity of the characteristic points, then reflected light intensity values of the corresponding pixel points in the turbid water body image are calculated according to the transmissivity and the fuzziness degrees of each pixel point, an enhanced image of the turbid water body image is obtained according to the reflected light intensity values and atmospheric light intensity values, the transmissivity of each pixel point in each local region is calculated, and the reflected light intensity values of the corresponding pixel points are calculated according to the transmissivity of the pixel points in each local region, and then, calculating the enhanced pixel value of each pixel point according to each reflected light intensity value and the atmospheric light intensity value of the turbid water body image, thereby realizing the accurate enhancement of each local area with different turbidity degrees and further improving the enhancement effect of the local area.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of the general steps of an embodiment of an image enhancement method for a turbid water body based on image processing.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In an embodiment of the method for enhancing an image of a turbid water body based on image processing, an application scenario of the embodiment is that local areas with different turbidity degrees may exist in the turbid water body image, and when a dark channel preoperative algorithm is used for enhancing, the image is integrally enhanced by using the same enhancement scale, and the local areas with different turbidity degrees cannot be adaptively enhanced, so that an enhancement effect is affected, so as shown in fig. 1, the method for enhancing the turbid water body based on image processing provided by the embodiment includes:
s1, obtaining a turbid water body image; specifically, an underwater detection device is used for collecting images of turbid water bodies.
Specifically, because the muddy condition of the water body can influence the imaging effect, the imaging effect needs to be enhanced, noise exists when the underwater camera is used for imaging the water body, and in order to avoid the influence of the noise on subsequent image processing, the noise reduction processing needs to be carried out on the image before the image enhancement.
S2, obtaining pixel difference values of each pixel point and adjacent pixel points in the turbid water body image, taking the maximum pixel difference value as the fuzzy degree of the corresponding pixel point, and clustering the pixel points according to the fuzzy degree difference values of each pixel point and adjacent pixel points to obtain a plurality of clustering areas.
Specifically, for a turbid water body, the transmittance of atmospheric light in a water body image is influenced mainly by the existence of a large number of floating objects in the water body, so that the image is blurred or shielded by the floating objects, and the quality of the image is poor.
The image enhancement by the dark channel prior defogging algorithm is the prior art and is mainly judged based on the imaging principle of a camera, and the imaging of the camera is mainly used for receiving the reflection of an object, such as for pixel points in the image
Which reflects light of
At this time, in the process of reflected light propagation, the floating object in the water body may block part of the reflected light, so as to attenuate the reflected light of the object, and at this time, the blocking degree of the floating object to the reflected light is the ratio of the reflected light reaching the camera to the reflected light of the object, that is, the transmittance is
Transmittance of
The larger the ratio of the reflected light, that is, the smaller the degree of shielding the reflected light in the turbid water image, the lower the turbidity of the turbid water.
Specifically, the pixel difference value of each pixel point and its neighborhood pixel point in the turbid water body image is obtained, and the maximum pixel difference value is used as the fuzzy degree of the corresponding pixel point.
Specifically, the step of clustering the pixel points according to the fuzzy degree difference of each pixel point and the neighborhood pixel points to obtain a plurality of cluster areas comprises: for turbid water body images of local areas with different turbidity degrees, different turbidities of different local areas are requiredEnhancing corresponding local areas by different scales according to the degree, and therefore, firstly determining the distribution of the turbidity degrees in the turbid water body image, namely setting a fuzzy degree difference threshold value; clustering the pixels with the fuzzy degree difference value between each pixel and each neighborhood pixel smaller than the fuzzy degree difference value threshold value and the neighborhood pixels to obtain a plurality of cluster regions, namely clustering the pixels
Degree of blur is noted as
Then pixel point
To (1) a
The fuzzy degree of each neighborhood pixel point is recorded as
Pixel point
And its adjacent pixel point
Corresponding to a difference in blur degree of
In this embodiment, the difference of the blur degrees is determined according to an empirical value
When the value of (2) is 5, when the pixel point is
And its adjacent pixel point
Corresponding difference in degree of blur
Difference in degree of blur
Then the pixel point is set
And its adjacent pixel point
And clustering into a cluster, and by analogy, clustering all pixel points in the turbid water body image to obtain a corresponding cluster.
In order to reduce the calculation amount, and because the fuzzy degree of the small-area cluster region has little influence on the fuzzy degree of the large-area cluster region, the area threshold of the cluster region is set first, the empirical value of the area threshold is 4, and the empirical value can be modified according to the actual condition; acquiring a target clustering region with the area smaller than an area threshold; acquiring the mean value of first fuzzy degree difference values of all pixel points of a target clustering region and the mean value of second fuzzy degree difference values of all pixel points of each clustering region in the neighborhood of the target clustering region; the mean value of the first fuzzy degree difference value and the mean value of each second fuzzy degree difference value are differentiated to obtain a mean value difference value; dividing the target clustering area into clustering areas corresponding to the minimum mean difference value to obtain a final clustering area; and taking the final cluster region as a cluster region, wherein the aim of the step is to divide local regions with different turbidity degrees of the turbid water body image.
And S3, taking the pixel point corresponding to the maximum fuzzy degree in the fuzzy degrees corresponding to all the pixel points in each cluster area as the characteristic point of the corresponding cluster area.
Specifically, a plurality of cluster regions are obtained in step S3
A cluster region is represented as a region of clusters,
wherein
Is shown as
The influence of floating objects in the water body in the floating process in the turbid water body image on the image is equivalent to the atomization effect of the image, so that the turbidity degree of the turbid water body image reflects the turbidity degree of the turbid water body image, and in order to reflect the turbidity degree of the local area, namely the turbidity degree of each cluster area, the cluster areas are clustered according to the blur degree of the turbid water body image
The bigger the turbid water body image is, the more turbid the turbid water body image is reflected, so that the pixel point corresponding to the maximum fuzzy degree in the fuzzy degrees corresponding to all the pixel points in each cluster region is used as the turbid degree characteristic point corresponding to the cluster region, the difference of the turbid degrees among different cluster regions is reflected by the fuzzy degree corresponding to the turbid degree characteristic point of the cluster region, and the characteristic point of each cluster region is obtained based on the difference.
And S4, acquiring a local dark channel map corresponding to each cluster area, acquiring an atmospheric light intensity value corresponding to each cluster area according to the local dark channel map, and taking the atmospheric light intensity value as an atmospheric light intensity value of the characteristic point of the cluster area.
Specifically, the step of obtaining the local dark channel map corresponding to each cluster region includes: setting a size of a cluster area corresponding to each characteristic point by taking each characteristic point as a center
The window of (1); obtaining the minimum value of all pixel points in the window in R, G, B three channels; obtain each windowAnd the minimum value of the three channels is minimally influenced by the reflected light of the object, so that the minimum value can reflect the atmospheric light intensity value to the greatest extent.
Specifically, the step of obtaining the atmospheric light intensity value corresponding to each cluster region according to the local dark channel map includes: taking pixel points which are less than 0.1% of the brightest value in the local dark channel image as target pixel points; and taking the maximum brightness value of the target pixel point in the turbid water body image as the atmospheric luminous intensity value of the cluster region.
S5, obtaining the transmissivity corresponding to the characteristic points according to the atmospheric light intensity values of the characteristic points, and calculating the transmissivity of each pixel point in the corresponding cluster area according to the transmissivity corresponding to the characteristic points of each cluster area and the fuzzy degree of each pixel point;
specifically, the transmittance in the image enhancement technology by using the dark channel prior defogging algorithm in the prior art reflects the turbidity degree, that is, the smaller the transmittance is, it indicates that suspended matter exists in the turbid water body image, and more other matters block light, so that the turbid water body of the turbid water body image is reflected, and for the situation that local areas with different turbidity degrees exist, the local areas should have different transmittances, so in this embodiment, the transmittance corresponding to the feature point is obtained according to the atmospheric light intensity value of the feature point, and the method for calculating the transmittance is a method for calculating the transmittance in the image enhancement technology by using the dark channel prior defogging algorithm, so this embodiment is not repeated.
When the reflected light intensity value of each cluster region is corrected by using the transmittance corresponding to the feature point, the enhanced cluster region obtained by calculating the reflected light intensity value of each cluster region can enhance the blocking phenomenon of the turbid water body image, that is, the reflected light intensity values of different cluster regions are different, so that the corresponding enhancement degrees are different, and further, the difference between the cluster region and the cluster region can be formed.
In order to avoid the occurrence of an obvious blocking phenomenon, specifically, the embodiment calculates the transmittance of each pixel point in the corresponding cluster region by using the transmittance corresponding to the feature point of each cluster region and the blur degree of each pixel point, and then calculates the ratio of the blur degree of the feature point of the cluster region to the blur degree of the pixel point in the cluster region; taking the product of the ratio of the fuzzy degree of the characteristic points of the cluster region to the fuzzy degree of the pixel points in the cluster region and the transmissivity corresponding to the characteristic points as the transmissivity of the pixel points, wherein the formula for calculating the transmissivity of each pixel point in the cluster region is as follows:
in the formula (I), the compound is shown in the specification,
is shown as
(ii) first of the clustered regions
The transmittance of each pixel point;
when needing to be explained, according to the steps 1 to 5, firstly, the corresponding fuzzy degrees of all the pixel points are calculated
Performing cluster analysis on pixel points, then obtaining characteristic points with local representativeness in each cluster region, representing the turbidity degree of the corresponding cluster region by the fuzzy degree (turbidity degree) corresponding to each characteristic point, accurately representing the turbidity degree of the image according to the transmittance in a dark channel pre-inspection algorithm, therefore, after obtaining the characteristic point of each cluster region of the turbid water body image, calculating the transmittance of the characteristic point according to a dark channel prior algorithm, then obtaining the transmittance of each pixel point by utilizing the transmittance of the characteristic point and the fuzzy degree of each pixel point in the cluster region corresponding to the characteristic point, namely, firstly determining the transmittance relation between the pixel point and the characteristic point according to the fuzzy degree relation between the pixel point and the characteristic point in each cluster region, thereby obtaining the transmittance of each pixel point, and calculating the reflected light intensity value in the cluster region for the subsequent calculation according to the transmittance of each pixel point in the cluster region, and avoids the blocking phenomenon of the turbid water body image.
S6, obtaining the reflected light intensity value of each pixel point of each cluster region in the turbid water body image according to the atmospheric light intensity value of each cluster region and the transmissivity of each pixel point in the cluster region, and obtaining the enhanced image of the turbid water body image according to the reflected light intensity values of all the pixel points and the atmospheric light intensity value of the turbid water body image.
Specifically, based on an image enhancement formula in the dark channel prior-inspection algorithm, a formula for obtaining an enhanced image of the turbid water body image according to the transmittance and the blur degree of each pixel point in local regions (cluster regions) with different turbidity degrees is obtained in the embodiment:
in the formula (I), the compound is shown in the specification,
first of turbid water body image
In a cluster area
The enhanced pixel values of the pixel points;
and taking the sum of the reflected light intensity value of each pixel point and the atmospheric light intensity value of the turbid water body image as the enhanced pixel value of the pixel point, and obtaining the enhanced image of the turbid water body image according to the enhanced pixel values of all the pixel points.
It should be noted that, in the following description,
is shown as
(ii) first of the clustered regions
The transmittance of the individual pixels is determined,
representing images of turbid water
In a cluster area
Determining the transmittance relation between the pixel points and the characteristic points according to the fuzzy degree relation between the pixel points and the characteristic points in each cluster region to obtain the transmittance of each pixel point, and then obtaining the enhancement of the turbid water body image according to the transmittance of the pixel points in each cluster region to the reflected light intensity value of the corresponding pixel point in the cluster region and the atmospheric light intensity value of the turbid water body imageThe image can realize the accurate enhancement of the turbid water body image, and further improve the enhancement effect.
In summary, the present invention provides a turbid water body image enhancement method based on image processing, which clusters pixel points through the ambiguity of the pixel points to obtain a plurality of cluster regions, and is intended to divide local regions of turbid water body images with different degrees of turbidity, then obtain characteristic points representing the degree of turbidity of each cluster region, obtain the transmittance of each pixel point in the cluster region according to the transmittance of the characteristic points, then calculate the reflected light intensity value of the corresponding pixel point in the turbid water body image according to the transmittance and the ambiguity of each pixel point, obtain the enhanced image of the turbid water body image according to the reflected light intensity value and the atmospheric light intensity value, realize the calculation of the transmittance of each pixel point in each local region, and calculate the reflected light intensity value of the corresponding pixel point through the transmittance of the pixel point in each local region, and then, calculating the enhanced pixel value of each pixel point according to each reflected light intensity value and the atmospheric light intensity value of the turbid water body image, thereby realizing the accurate enhancement of each local area with different turbidity degrees and further improving the enhancement effect of the local area.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (8)
1. A turbid water body image enhancement method based on image processing is characterized by comprising the following steps:
obtaining a turbid water body image;
acquiring a pixel difference value of each pixel point and a neighborhood pixel point in the turbid water body image, and taking the maximum pixel difference value as the fuzzy degree of the corresponding pixel point; clustering the pixel points according to the fuzzy degree difference of each pixel point and the neighborhood pixel points to obtain a plurality of cluster areas;
taking a pixel point corresponding to the maximum fuzzy degree in the fuzzy degrees corresponding to all pixel points in each cluster region as a characteristic point of the corresponding cluster region;
acquiring a local dark channel map corresponding to each cluster area, acquiring an atmospheric light intensity value corresponding to each cluster area according to the local dark channel map, and taking the atmospheric light intensity value as an atmospheric light intensity value of a characteristic point of the cluster area;
obtaining the transmissivity corresponding to the characteristic points according to the atmospheric light intensity values of the characteristic points, and calculating the transmissivity of each pixel point in the corresponding cluster area according to the transmissivity corresponding to the characteristic points of each cluster area and the fuzzy degree of each pixel point;
and obtaining a reflected light intensity value of each pixel point of each clustering region in the turbid water body image according to the atmospheric light intensity value of each clustering region and the transmissivity of each pixel point in the clustering region, and obtaining an enhanced image of the turbid water body image according to the reflected light intensity values of all the pixel points and the atmospheric light intensity value of the turbid water body image.
2. The turbid water body image enhancement method based on image processing according to claim 1, characterized in that the turbid water body image is an image obtained by denoising a turbid water body image by bilateral filtering.
3. The turbid water body image enhancement method based on image processing according to claim 1, wherein the step of clustering pixel points according to the fuzzy degree difference of each pixel point and its neighborhood pixel points to obtain a plurality of clustered regions comprises:
setting a fuzzy degree difference threshold value;
and clustering the pixels of which the fuzzy degree difference value between each pixel and each neighborhood pixel is smaller than the fuzzy degree difference value threshold and the neighborhood pixels to obtain a plurality of cluster regions.
4. The method for enhancing the turbid water body image based on the image processing as claimed in claim 2, further comprising:
setting an area threshold of a cluster region;
acquiring a target clustering region with the area smaller than an area threshold;
acquiring the mean value of first fuzzy degree difference values of all pixel points of a target clustering region and the mean value of second fuzzy degree difference values of all pixel points of each clustering region in the neighborhood of the target clustering region;
the mean value of the first fuzzy degree difference value and the mean value of each second fuzzy degree difference value are differentiated to obtain a mean value difference value;
dividing the target clustering area into clustering areas corresponding to the minimum mean difference value to obtain a final clustering area;
and taking the final cluster area as a cluster area.
5. The turbid water body image enhancement method based on image processing according to claim 1, wherein the step of obtaining the local dark channel map corresponding to each cluster region comprises:
setting a window in a clustering area corresponding to each characteristic point by taking each characteristic point as a center;
acquiring the minimum value of all pixel points in the window in an RGB three channel;
and acquiring a local dark channel image corresponding to each window, and taking the local dark channel image as a local dark channel image corresponding to the cluster area.
6. The turbid water body image enhancement method based on image processing as claimed in claim 1, wherein the step of obtaining the atmospheric light intensity value corresponding to each cluster region according to the local dark channel map comprises:
taking pixel points which are less than 0.1% of the brightest value in the local dark channel image as target pixel points;
and taking the corresponding maximum brightness value of the target pixel point in the turbid water body image as the atmospheric light intensity value of the cluster region.
7. The turbid water body image enhancement method based on image processing according to claim 1, wherein the step of calculating the transmittance of each pixel point in the corresponding cluster region according to the transmittance corresponding to the feature point of each cluster region and the blurring degree of each pixel point comprises:
calculating the ratio of the fuzzy degree of the characteristic points of the cluster region to the fuzzy degree of the pixel points in the cluster region;
and taking the product of the ratio of the fuzzy degree of the characteristic points of the cluster region to the fuzzy degree of the pixel points in the cluster region and the transmissivity corresponding to the characteristic points as the transmissivity of the pixel points.
8. The turbid water body image enhancement method based on image processing according to claim 1, wherein the step of obtaining the enhanced image of the turbid water body image according to the reflected light intensity values of all the pixel points and the atmospheric light intensity value of the turbid water body image comprises:
taking the sum of the reflected light intensity value of each pixel point and the atmospheric light intensity value of the turbid water body image as the pixel value of the pixel point after enhancement;
and obtaining an enhanced image of the turbid water body image according to the enhanced pixel values of all the pixel points.
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