CN112098289B - Device and method for measuring concentration of ocean suspended particulate matters based on digital image processing - Google Patents
Device and method for measuring concentration of ocean suspended particulate matters based on digital image processing Download PDFInfo
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Abstract
The invention provides a device and a method for measuring concentration of ocean suspended particles based on digital image processing, which are based on the principle of different reflectivities of seawater and ocean suspended particles to light and utilize a digital image processing technology to establish a set of device for measuring concentration of ocean suspended particles based on the digital image processing technology and an ocean suspended particle image characteristic value algorithm for representing the concentration of ocean suspended particles. The method tries to apply a digital image processing technology to the measurement of the concentration of the marine suspended particles, the measurement accuracy of the method only depends on the shooting accuracy of a measuring device and the improvement of a subsequent algorithm, the defect that the method is easily influenced by the particle size and the particle size distribution of the marine suspended particles can be overcome, and the method has the advantages of intuition, continuous observation, simplicity and convenience in operation and the like, and has wide application prospect in marine investigation.
Description
Technical Field
The invention belongs to the technical field of marine hydrological observation, and particularly relates to a device and a method for measuring concentration of marine suspended particulate matters based on digital image processing.
Background
The ocean suspended particulate matter generally refers to substances which can not pass through a filter membrane in specification in seawater, and comprises organic components serving as biological sources and inorganic components such as suspended silt. The marine suspended particles have double ecological effects, on one hand, the marine suspended particles are used as a place for microbial decomposition to release inorganic nitrogen and inorganic salt to a water body; on the other hand, the light-extinction type marine floating plant has an extinction effect, and influences photosynthesis of green phytoplankton in seawater through physical effects such as scattering and absorption of sunlight, so that the concentration of marine suspended particulate matters influences primary productivity in the ocean to a certain extent. In addition, the marine suspended particles are important factors for deeply knowing the marine sedimentation process, play an important role in the aspects of coastal erosion, sedimentation and the like, and the concentration change of the marine suspended particles is one of important parameters for marine environment dynamic research and is direct reflection of the movement processes of silt migration, sedimentation, resuspension and the like. In addition, the condition of suspended particles in the ocean water has a certain influence on the quality of the seawater and the reliability and service life of offshore structures such as offshore platforms and underwater pipelines. Therefore, the accurate measurement of the concentration of suspended particulate matters in the marine water body has great significance for the research on marine environment protection, marine engineering development, material migration and transportation and marine deposition dynamics.
The traditional measuring method for the concentration of the marine suspended particulate matters is widely applied, the measuring technology is relatively mature, but the traditional measuring method has the defects of insufficient measuring principle, such as: the optical method measurement process is greatly influenced by particle size, and a single-point measurement value cannot represent a concentration value of suspended particles on a section; calibration by an acoustic method is difficult and complicated in calculation; the laser diffraction method has a small measurement range, and the defects restrict the further development of the measurement of the concentration of the marine suspended particulate matters. In the conventional marine hydrological investigation, a transmissometer or a turbidimeter is commonly used to measure the change of the concentration of suspended particulate matters in seawater, and the transmissometer and the turbidimeter reflect the concentration of the suspended particulate matters in seawater by measuring the attenuation or reflection of a light beam in the seawater based on the principle of optical measurement. The optical-based measuring method is easily influenced by soluble substances in seawater, and the attenuation amount or the reflection amount of a light beam is lost to a certain extent, so that a certain error exists in a measuring result; due to the limitation of the measurement principle, the transmissometer is sensitive to coarse particulate matters, and the turbidimeter is sensitive to fine particulate matters, so that the accuracy of the measurement result is always influenced by the uneven distribution of the particle sizes of the marine particles; in addition, biological factors also often affect the accuracy of optical measurement, so that the measurement result has errors. Therefore, the method for accurately measuring the concentration of suspended particulate matters in seawater needs to be further researched and solved.
Disclosure of Invention
In order to make up for the defects of the prior art, the invention provides a device and a method for measuring the concentration of marine suspended particles based on digital image processing.
The invention is realized by the following technical scheme: a device for measuring the concentration of ocean suspended particles based on digital image processing comprises a data acquisition and storage pressure-resistant cabin and a combined equipment integration frame, and is characterized in that the top end of the data acquisition and storage pressure-resistant cabin is connected with an upper pressure-resistant cabin sealing end cover through a bolt, the bottom end of the data acquisition and storage pressure-resistant cabin is connected with a lower pressure-resistant cabin sealing end cover through a bolt, the lower surface of the lower pressure-resistant cabin sealing end cover is fixedly provided with the combined equipment integration frame, the combined equipment integration frame comprises a mounting disc, the upper surface of the mounting disc is fixedly connected with the lower surface of the lower pressure-resistant cabin sealing end cover, the edge of the mounting disc is connected with a plurality of connecting rods through bolts, the bottom ends of the connecting rods are fixedly connected with a supporting ring, the center of the lower surface of the mounting disc is provided with ocean high-resolution camera equipment, the lens direction of, still fixed three ocean camera auxiliary lighting equipment of being equipped with on the lower surface of installation disc, ocean camera auxiliary lighting equipment uses ocean high resolution camera equipment to be regular trilateral distribution and uses 120 contained angles installation as the center, is connected with angle adjusting device through the transmission shaft on ocean camera auxiliary lighting equipment's the outer wall.
As a preferred scheme, the data acquisition and storage pressure-resistant cabin is characterized in that a shell of the data acquisition and storage pressure-resistant cabin is a pressure-resistant cabin wall, an inner cavity of the data acquisition and storage pressure-resistant cabin is composed of an upper power supply unit and a lower data acquisition and storage circuit board, the data acquisition and storage circuit board is assembled through a circuit board integration support, a single chip microcomputer, a solid state disk, a WiFi signal transmitting device and a signal receiving device are arranged in the data acquisition and storage circuit board, and the single chip microcomputer controls and is connected with an electric motor in the angle.
Preferably, the material of the combined equipment integrated frame is 316L stainless steel material.
Preferably, the marine high-resolution camera device is internally provided with a high-resolution CCD sensor, the number of pixels of the marine high-resolution camera device is 1200 ten thousand, the marine high-resolution camera device is packaged by a 316L stainless steel shell, an aluminum alloy hard oxidation material is used as a lens shell material, a lens is packaged and protected by a rubber spiral cover, the diameter of the lens is 51 mm, and the length of the lens is 180 mm.
Preferably, the camera auxiliary lighting device is an LED lamp, the camera auxiliary lighting device is packaged by a 316L stainless steel shell, an aluminum alloy hard oxidation material is used as a shell material of the illuminating lamp, and the illuminating lamp is packaged and protected by a rubber spiral cover.
A method of a device for measuring the concentration of ocean suspended particles based on digital image processing comprises the following steps:
s1: performing frame processing on the video shot by the device, and then processing each frame of image;
s2: performing geometric operation on the image; intercepting each frame of image of the obtained video by the same operation, so as to ensure the consistency of the processing process;
s3: graying the image; in the color image RGB model, for R = G = B, its corresponding gray value is equal to the RGB value; for color images of unequal RGB, it needs to be calculated according to the ITU standard defined by the International Telecommunication Union (ITU) (ITU/EBU 3213 standard), namely:
Gray(i,j)=0.222015*R(i,j)+0.706655*G(i,j)+0.071330*B(i,j)
obtaining an image graying result;
s4: enhancing the image; firstly, a minimum value filter w1 is used for extracting the darkest point in the pixel field, and the calculation formula is as follows: r = min { Z { (B) }kI k =1,2,. n }, resulting in an initial background map; the image is then smoothed by a mean filter w2, whose filter calculation formula is:
obtaining a final background picture; finally, subtracting the final background image from the original gray image to obtain an enhanced image; wherein w1 and w2 take the same value, i.e. w = w1= w2, the size of which is the best value selected by the indoor experimental alignment, the window size is odd, and the minimum value starts from 3;
s5: a morphological algorithm; firstly, building structural body elements, wherein a disk-shaped structural body is selected as ocean suspended particles are oval or round, and the size of the structural body is finally obtained according to repeated test comparison; then, carrying out corrosion operation on the image, and then carrying out expansion operation, namely completing the opening operation of the structure body Se on the original image f to obtain a background image; finally, subtracting the two images, namely subtracting the background image from the original gray image to obtain a final image;
s6: performing image binarization, namely performing binarization on an image by using a threshold processing technology, wherein any satisfied point is called an object point and other points are called background points by selecting a threshold T, and the image after threshold processing is defined as:
in the formula: pixels of g (x, y) =1 correspond to the target object, and pixels of g (x, y) =0 refer to the image background;
s7: extracting image information; the characteristic value and the turbidity value corresponding to the water depth are subjected to the linear transformation by using a min-max standardization method until all values fall to [0, 1 ]]Namely:and respectively processing the finally processed normalized characteristic value and the normalized turbidity value along a profile curve of the water depth.
Preferably, in step S6, the threshold T is processed by an Otus method, an iterative threshold method, and a region growing method, and the processing result is compared and analyzed to finally determine an optimal threshold algorithm suitable for image processing.
Further, the Otus method comprises the following specific steps: for an image I (x, y), a segmentation threshold value of a foreground, namely a target and a background is recorded as T, the proportion of the number of pixel points belonging to the foreground in the whole image is recorded as omega 0, and the average gray value is recorded as mu 0; the proportion of the number of background pixels to the whole image is omega 1, and the average gray value is recorded as mu 1; the total average gray value of the image is recorded as mu, and the inter-class variance is recorded as g; assuming that the background of the image is dark and M × N, the number of pixels in the image with the gray level smaller than the threshold T is N0, and the number of pixels with the gray level larger than the threshold T is N1, the following are:
ω0=N0/M×N
ω1=N1/M×N
ω0+ω1=1
μ=ω0×μ0+ω1×μ1
g=ω0(μ0-μ)2+ω1(μ1-μ)2
the above formulas are arranged to obtain an equivalent formula, namely, the inter-class variance g = omega0ω1(μ0-μ1)2And repeatedly and circularly calculating to obtain the maximum value of the class variance, namely obtaining the threshold value T finally used for segmenting the image.
Further, the iterative threshold method specifically comprises the following steps:
s61: setting a parameter T0, and selecting an initial estimated value T1;
s62: dividing the image into two parts by using a threshold value T1; g1 is composed of pixels having a grayscale value greater than T1, G2 is composed of pixels having a grayscale value less than or equal to T2;
s63, calculating average gray values mu 1 and mu 2 of all pixels in G1 and G2 and a new threshold value T2=(μ1+μ2)/2;
S64 if | T2-T1|<T0Then, push out T2Is an optimal threshold value; otherwise, will T2Is assigned to T1And repeating S62-S64 until an optimal threshold is obtained.
Further, the region growing method uses the gray level difference between adjacent pixels of the image as a similarity criterion, namely: l f (x)1,y1)- f(x2,y2) In the formula, I is less than or equal to T: and T is a threshold value set according to the image characteristics to obtain an image binarization algorithm result.
Due to the adoption of the technical scheme, compared with the prior art, the invention has the following beneficial effects: the invention provides a device and a method for measuring the concentration of ocean suspended particles based on digital image processing, which apply the digital image processing technology to the measurement of the concentration of the ocean suspended particles, the measurement precision of the method only depends on the shooting precision of a measuring device and the improvement of a subsequent algorithm, and the principle defects of the traditional technology for measuring the concentration of the ocean suspended particles are overcome, such as: the device has the advantages of being easy to be influenced by the particle size of the marine suspended particles, the particle size distribution of the marine suspended particles and the like, and the influence of the particle size and the particle size distribution, and the like, and meanwhile, the device has the advantages of being visual, continuous in observation, simple and convenient to operate and the like, so that the device has a wide application prospect in marine investigation. The method has the advantages that the digital image processing technology is popularized to the field of observing the concentration of ocean suspended particles, the intersection of multiple disciplinary fields is reflected, and the method has good research and reference significance.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic front view of the present invention;
FIG. 2 is a schematic bottom perspective view of the present invention;
FIG. 3 is a bottom partially enlarged view of the present invention;
FIG. 4 is a schematic top view of the present invention;
FIG. 5 is a schematic bottom view of the present invention;
FIG. 6 is a schematic diagram of the internal structure of the data acquisition and storage pressure-resistant cabin;
FIG. 7 is a video image processing flow diagram;
FIG. 8 is a graph of the video image graying processing result;
FIG. 9 is a flow chart of a video image enhancement process;
FIG. 10 is a comparison graph of the processing effect of the video image enhancement algorithm;
FIG. 11 is a flow chart of a video image morphology algorithm process;
FIG. 12 is a graph of the processing results of the video image morphological algorithm;
FIG. 13 is a diagram of the result of the binarization algorithm processing of the video image;
FIG. 14 is a graph of the comparison of normalized feature values and normalized turbidity values of video images,
wherein, the corresponding relationship between the reference numbers and the components in fig. 1 to fig. 6 is:
the device comprises a data acquisition and storage pressure-resistant cabin, a 1-1 power supply unit, a 1-2 data acquisition and storage circuit board, a 1-3 pressure-resistant cabin wall, a 1-4 circuit board integrated support, a 2 combined equipment integrated frame, a 3 pressure-resistant cabin upper sealing end cover, a 4 pressure-resistant cabin lower sealing end cover, 5 bolts, 6 mounting discs, 7 connecting rods, 8 supporting rings, 9 ocean high-resolution camera equipment, 10 clamping devices, 11 ocean camera auxiliary lighting equipment and 12 angle adjusting devices.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced otherwise than as specifically described herein, and thus the scope of the present invention is not limited by the specific embodiments disclosed below.
The apparatus and method for measuring the concentration of marine suspended particulate matter based on digital image processing according to the embodiments of the present invention will be described in detail with reference to fig. 1 to 14. The device is used for obtaining high-quality marine suspended particle images, the quality of the marine suspended particle images has great influence on the establishment of a subsequent marine suspended particle image characteristic value algorithm, the high-quality marine suspended particle images can simplify the steps and the processing flow of the algorithm, the image processing speed is improved, when the image quality is low, the processing efficiency is low, and the accuracy of the inversion of the concentration data of the subsequent marine suspended particle images is also greatly influenced. The quality of acquiring the marine suspended particle images is mainly influenced by the complex marine shooting environment (such as serious light loss, uneven illumination, influence of marine organism activities and the like) and the shooting performance of the marine image acquisition device.
As shown in fig. 1 to 6, the present invention proposes that the present invention is realized by the following technical solutions: the utility model provides an ocean suspended particles concentration survey device based on digital image processing, is withstand voltage cabin 1, combined equipment integrated frame 2 including data acquisition storage, and the material of combined equipment integrated frame 2 is 316L stainless steel material, can guarantee ocean suspended particles camera device and shoot in-process safety and stability. The top end of the data acquisition and storage pressure-resistant cabin 1 is connected with a pressure-resistant cabin upper sealing end cover 3 through a bolt, the bottom end of the data acquisition and storage pressure-resistant cabin 1 is connected with a pressure-resistant cabin lower sealing end cover 4 through a bolt, a combined equipment integrated frame 2 is fixedly installed on the lower surface of the pressure-resistant cabin lower sealing end cover 4, the combined equipment integrated frame 2 comprises an installation disc 6, the upper surface of the installation disc 6 is fixedly connected with the lower surface of the pressure-resistant cabin lower sealing end cover 4, the edge of the installation disc 6 is connected with a plurality of connecting rods 7 through bolts 5, the bottom end of each connecting rod 7 is fixedly connected with a supporting ring 8, a marine high-resolution camera 9 is installed at the center of the lower surface of the installation disc 6, the lens direction of the marine. The outer wall of the ocean high-resolution camera equipment 9 is provided with a clamping device 10 and is fixedly arranged on the lower surface of the installation disc 6, the lower surface of the installation disc 6 is also fixedly provided with three ocean camera auxiliary lighting equipment 11, the ocean camera auxiliary lighting equipment 11 is regularly distributed by taking the ocean high-resolution camera equipment 9 as a center and is installed at an included angle of 120 degrees, the outer wall of the ocean camera auxiliary lighting equipment 11 is connected with an angle adjusting device 12 through a transmission shaft, the side edge of the ocean high-resolution camera equipment 9 irradiates at an angle of 30-60 degrees, each ocean camera auxiliary lighting equipment is connected with the angle adjusting device through the transmission shaft, and the angle adjusting device can control an electric motor inside the ocean camera auxiliary lighting equipment through a control circuit single chip microcomputer, so that the adjustment of a measurement angle is realized.
The installation angle of the power supply of the ocean high-resolution camera equipment 9 and the ocean camera auxiliary lighting equipment 11 greatly influences the illumination distribution of the shooting field of view, so that the acquisition quality of ocean suspended particulate matter images can influence the inversion result of the subsequent ocean suspended particulate matter concentration finally, and the data are unreliable. Therefore, the positions and the installation angles of the marine high-resolution camera device 9 and the marine camera auxiliary lighting device 11 should be reasonably designed, so that the optimal marine suspended particle images can be obtained by uniform and full illumination distribution in the shooting field of view, and the reliability of the inversion result can be ensured. The experimental laboratory results show that when the auxiliary lighting equipment of the ocean camera irradiates along the shooting direction at an inclined angle of 30-60 degrees, the obtained image is uniform and full, and the image quality is optimal. The observation device of the invention is directly used for lowering measurement by using the A-shaped frame of the marine scientific research ship or is integrated in other marine observation platforms for synchronous measurement. The device not only can reach the best quality of shooing of the ocean suspended particles image of on-the-spot collection, and whole collection system is located the stainless steel shell frame of 316L material moreover, can guarantee ocean suspended particles camera device and shoot the in-process safety and stability.
The data acquisition and storage pressure-resistant cabin comprises a data acquisition and storage pressure-resistant cabin 1, wherein a shell of the data acquisition and storage pressure-resistant cabin 1 is a pressure-resistant cabin wall 1-3, an inner cavity of the data acquisition and storage pressure-resistant cabin 1 is composed of an upper power supply unit 1-1 and a lower data acquisition and storage circuit board 1-2, the upper power supply unit 1-1 is used for supplying power to a lower data acquisition and storage circuit board-12, the data acquisition and storage circuit board 1-2 is assembled through a circuit board integrated support 1-4, a single chip microcomputer, a solid state disk, a WiFi signal transmitting device and a signal receiving device are arranged in the data acquisition and storage circuit board 1-2, and the lower data acquisition and storage circuit board can realize functions of data acquisition. The data acquisition and power supply unit control is realized through a single chip microcomputer, the data storage is realized through a built-in high-capacity solid state hard disk to store seabed camera shooting data and data processing results, the WiFi signal connection control is realized through a built-in WiFi signal transmitting device and a built-in signal receiving device to control functions of internal data acquisition, data processing, data storage, power supply unit control and the like, the requirements of parameter setting, data exporting, external debugging and the like can be met, and meanwhile, a complicated program that an external watertight socket is connected with a computer is avoided. When the device is used, wireless communication between external equipment and the device can be realized only by connecting a WiFi signal of the pressure-resistant cabin with a mobile phone or a computer. The single chip microcomputer controls an electric motor connected to the inside of the angle adjusting device 12, thereby realizing adjustment of the measurement angle.
The ocean high-resolution camera equipment 9 is internally provided with a high-resolution CCD sensor, the number of pixels of the CCD sensor is 1200 ten thousand, and high-quality shooting of ocean suspended particulate matter images can be realized. The marine high-resolution camera equipment 9 is packaged by a 316L stainless steel shell, an aluminum alloy hard oxidation material is used as a lens shell material, and a lens is protected by a rubber spiral cover in a packaging way, wherein the diameter of the lens is 51 mm, and the length of the lens is 180 mm. The marine high-resolution camera 9 is small in size, easy to install and distribute, high in pressure resistance and corrosion resistance, and capable of working and using in a marine environment with the depth of 2000 m.
The camera auxiliary lighting device 11 is an LED lamp, which has advantages of long life, small size, low power consumption, high light efficiency, no flash frequency, and the like compared to other types of lighting lamps. The auxiliary illuminating lamp of the ocean camera can improve the shooting environment of the ocean camera, so that the high-quality ocean suspended particulate matter video image can be obtained in the ocean environment with serious light attenuation. The camera auxiliary lighting device 11 is packaged by a 316L stainless steel shell, an aluminum alloy hard oxidation material is used as a shell material of the lighting lamp, and the lighting lamp is packaged and protected by a rubber spiral cover. The packaged auxiliary illuminating lamp for the ocean camera also has high pressure resistance and corrosion resistance, and the working depth of the auxiliary illuminating lamp can reach 2000 m.
A processing method of a device for measuring the concentration of suspended marine particles based on digital image processing is disclosed, as shown in figure 7, the suspended marine particles of a target body can be observed visually through high-resolution marine video image data obtained by the device for measuring the concentration of suspended marine particles based on image processing technology, however, the vertical distribution condition of suspended sand cannot be obtained quantitatively only by naked eyes, and the digital image processing technology can provide a solution for the post processing of collected underwater video images. The invention is based on digital image processing technology, realizes a series of processing to video images through a built-in data processing circuit board, firstly carries out frame processing to the video, and then carries out processing to each frame of image, and comprises the following steps: geometric operation of an image, graying, image enhancement and image binarization processing. The image enhancement adopts two processing means of an algorithm based on airspace and an algorithm based on morphology respectively, and selects an optimal algorithm according to a processing result; the image binarization processing adopts three processing means of an Otus threshold segmentation method, an iterative threshold method and a region growing method respectively, and the optimal value is selected by comparison according to the processing result. The method comprises the following specific steps:
s1: performing frame processing on the video shot by the device, and then processing each frame of image;
s2: performing geometric operation on the image; intercepting each frame of image of the obtained video by the same operation, so as to ensure the consistency of the processing process;
the auxiliary lighting devices of the marine cameras on the two sides of the marine high-resolution camera device provide sufficient and uniform soft light for the shooting view field of the camera, however, in the whole dark deep sea environment, two sides of the shot image are basically in a dark state, so that geometric operation needs to be carried out on the image, and the area to be processed is selected for subsequent processing.
S3: graying the image; in the color image RGB model, for R = G = B, its corresponding gray value is equal to the RGB value; for color images of unequal RGB, it needs to be calculated according to the ITU standard defined by the International Telecommunication Union (ITU) (ITU/EBU 3213 standard), namely:
Gray(i,j)=0.222015*R(i,j)+0.706655*G(i,j)+0.071330*B(i,j)
obtaining the image graying result, as shown in fig. 8;
the image graying refers to converting a color image into a grayscale image, wherein the color of each pixel in the color image is composed of R, G, B three components, each component has 255 gray-scale values, while the grayscale image is a special image with the same gray-scale values of the three components, and the grayscale image can still reflect the overall and local brightness and chrominance characteristics of the image. In the process of digital image processing, the color image is converted into a gray image, so that the complexity of the image, the information processing amount and the calculation amount of subsequent image processing are reduced.
S4: enhancing the image; as shown in fig. 9, the darkest point in the pixel area is first extracted by a minimum value filter w1, which is calculated by the formula: r = min { Z { (B) }kI k =1,2,. n }, resulting in an initial background map; the image is then smoothed by a mean filter w2, whose filter calculation formula is:obtaining a final background picture; finally, subtracting the final background image from the original gray image to obtain an enhanced image; wherein w1 and w2 take the same value, i.e. w = w1= w2, the size of which is the best value selected by the indoor experimental alignment, the window size is odd, and the minimum value starts from 3; obtaining an image enhancement result, wherein (a) is an original gray scale map; (b) is w = 3; (c) is w = 5; (d) w = 7, as shown in fig. 10.
The image enhancement means selectively highlighting 'useful' information needing to be highlighted in the image, attenuation unnecessary information or interference information to enhance the difference between the target volume characteristics and the background, so that the subsequent operations of target volume characteristic extraction and the like are facilitated, and the image quality degradation is not considered in the operation process. The technology can be divided into two categories of algorithms based on airspace or frequency according to different processing spaces. Wherein, the spatial domain method is to directly operate on the image; whereas the frequency domain rule operates within some transform domain of the image. In addition, the aim of image enhancement can be achieved by the morphological algorithm based on the image. The method adopts an algorithm based on a space domain and a gray level image morphology algorithm to realize the enhancement of the image.
The preprocessed gray level image needs image enhancement because the target body features are not prominent, and if the target body features are directly extracted, the expected effect cannot be achieved. By observing the gray scale image, the target body (the marine suspended particulate matter) is found to have a strong gray scale relative to the background (the marine water body). The function principle of the minimum value filter is to find the minimum value in the neighborhood of the pixel to be processed and endow the value with the brightness value of the pixel point to be processed, so as to find the darkest point in the neighborhood, and the calculation formula is as follows: r = min { Z { (B) }kI k =1,2, ·, n }; the function principle of the mean filter is to calculate the average value of each pixel in the neighborhood, and assign the average value as the brightness value of the central point, the template matrix coefficients are all 1, and for the window template of (2 k + 1) × (2 k + 1), the filtering calculation formula is as follows:the method is mainly used for smoothing the image, the smoothing effect of the average filtering is positively correlated with the filtering radius, the larger the filtering radius is, the better the smoothing effect is, and the more fuzzy the image is.
S5: a morphological algorithm; as shown in fig. 11, firstly, a structural element is created, and since the marine suspended particulate matter is elliptical or circular, a disk-shaped structural body is selected, and the size of the structural body needs to be finally obtained according to repeated test comparison; then, carrying out corrosion operation on the image, and then carrying out expansion operation, namely completing the opening operation of the structure body Se on the original image f to obtain a background image; finally, subtracting the two images, namely subtracting the background image from the original gray image to obtain a final image;
mathematical morphology is to use a certain structural element to obtain the relationship between the whole and part of the image as the structure moves in the image, so as to obtain the characteristic structure of the image. The basic morphological algorithms include dilation and erosion, open and close operations, according to which the aim of image enhancement can be achieved. Based on the principle of morphological algorithm, the method obtains the result of morphological algorithm according to the characteristics of the target body marine suspended particles in the original gray level image, as shown in fig. 12.
S6: performing image binarization, namely performing binarization on an image by using a threshold processing technology, wherein any satisfied point is called an object point and other points are called background points by selecting a threshold T, and the image after threshold processing is defined as:
in the formula: the pixel of g (x, y) =1 corresponds to the target object, and the pixel of g (x, y) =0 refers to the image background, resulting in the image binarization algorithm result, as shown in fig. 13;
after a series of previous processes, particles in the image are already highlighted, however, a subsequent analysis of a desired target in the image is required, and an image binarization process, that is, a segmentation process is required to be performed on the image, that is, an image is divided into two parts, namely a target and a background. The segmentation algorithm of the gray image is generally based on the discontinuity or similarity of the image brightness, wherein the processing method of the discontinuity characteristic is to segment one image by the abrupt change of the image brightness, such as the segmentation according to the edge detection; the similarity is obtained by dividing the image into similar regions according to a predefined criterion. The invention adopts the second mode and utilizes the threshold processing technology to carry out binarization on the image.
And processing the image by adopting an Otus method, an iterative threshold method and a region growing method, comparing and analyzing the processing result and finally determining the optimal threshold algorithm suitable for image processing.
The Otus method is also called a maximum inter-class variance method, and finds a threshold value corresponding to the maximum inter-class variance g based on a gray histogram of the image. The method comprises the following specific steps: for an image I (x, y), a segmentation threshold value of a foreground, namely a target and a background is recorded as T, the proportion of the number of pixel points belonging to the foreground in the whole image is recorded as omega 0, and the average gray value is recorded as mu 0; the proportion of the number of background pixels to the whole image is omega 1, and the average gray value is recorded as mu 1; the total average gray value of the image is recorded as mu, and the inter-class variance is recorded as g; assuming that the background of the image is dark and M × N, the number of pixels in the image with the gray level smaller than the threshold T is N0, and the number of pixels with the gray level larger than the threshold T is N1, the following are:
ω0=N0/M×N
ω1=N1/M×N
ω0+ω1=1
μ=ω0×μ0+ω1×μ1
g=ω0(μ0-μ)2+ω1(μ1-μ)2
the above formulas are arranged to obtain an equivalent formula, namely, the inter-class variance g = omega0ω1(μ0-μ1)2And repeatedly and circularly calculating to obtain the maximum value of the class variance, namely obtaining the threshold value T finally used for segmenting the image.
The iterative threshold method is to calculate the optimal threshold value of the segmentation by an iterative method, and the iterative threshold method comprises the following specific steps:
s61: setting a parameter T0, and selecting an initial estimated value T1;
s62: dividing the image into two parts by using a threshold value T1; g1 is composed of pixels having a grayscale value greater than T1, G2 is composed of pixels having a grayscale value less than or equal to T2;
s63, calculating average gray values mu 1 and mu 2 of all pixels in G1 and G2 and a new threshold value T2=(μ1+μ2)/2;
S64 if | T2-T1|<T0Then, push out T2Is an optimal threshold value; otherwise, will T2Is assigned to T1And repeating S62-S64 until an optimal threshold is obtained.
Region growing refers to the process of grouping pixels or sub-regions into larger regions according to a predefined criterion. The method realizes the region growth based on the region gray level difference criterion according to the characteristics of the image to be processed. The region growing method takes the gray level difference between adjacent pixels of the image as a similarity criterion, namely: l f (x)1,y1)- f(x2,y2) In the formula, I is less than or equal to T: and T is a threshold value set according to the image characteristics to obtain an image binarization algorithm result.
S7: extracting image information; the processed image is a binary image, wherein the target body is pixel points with all gray values of 1, the number of all the pixel points in the image with all the gray values of 1 is calculated through analyzing and processing the binary image, and the proportion of the suspended particulate matters of the target body in the water body can be obtained, so that the extraction of the area factors of the image particles is realized.
The characteristic value calculated by the image processing method and the turbidity value acquired by the turbidity meter can not directly reflect the concentration of suspended particles in the water body, the characteristic value and the turbidity value have different dimensional levels, and the characteristic value and the turbidity value acquired by the turbidity meter can not be directly compared along a profile curve of the water depth, so that the characteristic value and the turbidity value of the corresponding water depth are linearly transformed by a min-max standardization method, and all values fall to [0, 1 ] in the process of linearly transforming the original data]Namely:and respectively processing the finally processed normalized characteristic value and the normalized turbidity value along a profile curve of the water depth.
In the description of the present invention, the terms "plurality" or "a plurality" refer to two or more, and unless otherwise specifically limited, the terms "upper", "lower", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are merely for convenience in describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present invention; the terms "connected," "mounted," "secured," and the like are to be construed broadly and include, for example, fixed connections, removable connections, or integral connections; may be directly connected or indirectly connected through an intermediate. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the description herein, the description of the terms "one embodiment," "some embodiments," "specific embodiments," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes will occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (5)
1. A method of a device for measuring the concentration of ocean suspended particles based on digital image processing is characterized by comprising the following specific steps:
s1: performing frame processing on the video shot by the device, and then processing each frame of image;
s2: performing geometric operation on the image; intercepting each frame of image of the obtained video by the same operation, so as to ensure the consistency of the processing process;
s3: graying the image; in the color image RGB model, for R = G = B, its corresponding gray value is equal to the RGB value; for color images of unequal RGB, it needs to be computed according to the ITU standard ITU/EBU 3213 standard defined by the International Telecommunication Union (ITU), namely:
Gray(i,j)=0.222015*R(i,j)+0.706655*G(i,j)+0.071330*B(i,j)
obtaining an image graying result;
s4: enhancing the image; firstly, a minimum value filter w1 is used for extracting the darkest point in the pixel field, and the calculation formula is as follows: r = min { Z { (B) }kI k =1,2,. n }, resulting in an initial background map; the image is then smoothed by a mean filter w2, whose filter calculation formula is:
obtaining a final background picture; finally, subtracting the final background image from the original gray image to obtain an enhanced image; wherein w1 and w2 take the same value, i.e. w = w1= w2, the size of which is the best value selected by the indoor experimental alignment, the window size is odd, and the minimum value starts from 3;
s5: a morphological algorithm; firstly, building structural body elements, wherein a disk-shaped structural body is selected as ocean suspended particles are oval or round, and the size of the structural body is finally obtained according to repeated test comparison; then, carrying out corrosion operation on the image, and then carrying out expansion operation, namely completing the opening operation of the structure body Se on the original image f to obtain a background image; finally, subtracting the two images, namely subtracting the background image from the original gray image to obtain a final image;
s6: performing image binarization, namely performing binarization on an image by using a threshold processing technology, wherein any satisfied point is called an object point and other points are called background points by selecting a threshold T, and the image after threshold processing is defined as:
in the formula: pixels of g (x, y) =1 correspond to the target object, and pixels of g (x, y) =0 refer to the image background;
s7: extracting image information; the characteristic value and the turbidity value corresponding to the water depth are subjected to line drawing on the original data by utilizing a min-max standardization methodSex transformations bringing all values to [0, 1 ]]Namely:and respectively processing the finally processed normalized characteristic value and the normalized turbidity value along a profile curve of the water depth.
2. The method for determining concentration of marine suspended particulate matters based on digital image processing according to claim 1, wherein the threshold value T in the step S6 is obtained by processing the image by an Otus method, an iterative threshold value method and a region growing method, and comparing and analyzing the processing results to finally determine an optimal threshold value algorithm suitable for image processing.
3. The method for determining the concentration of suspended particulate matters in the ocean based on digital image processing as claimed in claim 2, wherein the Otus method comprises the following steps: for an image I (x, y), a segmentation threshold value of a foreground, namely a target and a background is recorded as T, the proportion of the number of pixel points belonging to the foreground in the whole image is recorded as omega 0, and the average gray value is recorded as mu 0; the proportion of the number of background pixels to the whole image is omega 1, and the average gray value is recorded as mu 1; the total average gray value of the image is recorded as mu, and the inter-class variance is recorded as g; assuming that the background of the image is dark and M × N, the number of pixels in the image with the gray level smaller than the threshold T is N0, and the number of pixels with the gray level larger than the threshold T is N1, the following are:
ω0=N0/M×N
ω1=N1/M×N
ω0+ω1=1
μ=ω0×μ0+ω1×μ1
g=ω0(μ0-μ)2+ω1(μ1-μ)2
the above formulas are arranged to obtain an equivalent formula, namely, the inter-class variance g = omega0ω1(μ0-μ1)2By repeatedly cycling through calculationsAnd obtaining the maximum value of the class variance, namely obtaining the threshold value T finally used for segmenting the image.
4. The method for determining the concentration of the marine suspended particulate matters based on the digital image processing as claimed in claim 2, wherein the iterative threshold method comprises the following specific steps:
s61: setting a parameter T0, and selecting an initial estimated value T1;
s62: dividing the image into two parts by using a threshold value T1; g1 is composed of pixels having a grayscale value greater than T1, G2 is composed of pixels having a grayscale value less than or equal to T2;
s63, calculating average gray values mu 1 and mu 2 of all pixels in G1 and G2 and a new threshold value T2=(μ1+μ2)/2;
S64 if | T2-T1|<T0Then, push out T2Is an optimal threshold value; otherwise, will T2Is assigned to T1And repeating S62-S64 until an optimal threshold is obtained.
5. The method for determining the concentration of the marine suspended particles based on the digital image processing as claimed in claim 2, wherein the region growing method uses the gray level difference between the adjacent pixels of the image as a similarity criterion, namely:
|f(x1,y1)- f(x2,y2)|≤T,
in the formula: and T is a threshold value set according to the image characteristics to obtain an image binarization algorithm result.
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