Underwater oil spill imaging detection method and equipment based on polarization correlation algorithm

Abstract

The present application discloses a method and device for underwater oil spill imaging detection based on a polarization correlation algorithm, relating to the field of underwater target detection imaging technology. The method comprises: calculating a polarization correlation image based on the horizontal polarization intensity and vertical polarization intensity of a reflected laser signal; obtaining a polarization image based on the polarization correlation image, and calculating the linear polarization degree of different regions; obtaining the intensity value of the reflected laser signal and the intensity of background scattered light based on the polarization correlation image, the linear polarization degree of the oil spill detection region, and the background region; calculating a correction factor for the reflected laser signal based on the polarization correlation image and the background scattered light intensity; determining a transmission function based on the polarization intensity, the background scattered light intensity, the linear polarization degree of the background region, and the correction factor; and determining a de-scattered restored image based on the transmission function, the background scattered light intensity, and the intensity value of the reflected laser signal. The present application improves the image quality and reliability of sea surface oil spill detection imaging.

Description

Technical Field

[0001] The present application relates to the technical field of underwater target detection and imaging, and in particular to an underwater oil spill imaging detection method and device based on a polarization correlation algorithm. Background Art

[0002] An oil spill is a marine emergency caused by the release of crude oil or oil products due to accidents or operational errors during offshore oil exploration, development, and transportation. With China's rapid economic development, demand for petroleum energy continues to grow, and offshore oil resource development, transportation, and storage activities are increasing, increasing the risk of marine oil spills. China is a major importer of crude oil, and according to statistics, 90% of this crude oil is transported by sea. Marine oil spills are the most typical and serious environmental pollution accidents in human development of the ocean. Once they occur, the resulting pollution is extremely destructive to the marine environment and marine biological resources. If oil slicks are washed ashore by wind and waves, they can also pollute shorelines and mudflats, damage aquaculture, affect coastal tourism, and threaten human health.

[0003] During offshore oil production operations, surface oil spills pose a significant safety and environmental risk in daily production management. Timely detection and early warning can lead to early detection and remediation, thereby reducing pollution to the marine environment and associated economic losses. Advances in remote sensing technology, such as synthetic aperture radar (SAR), multispectral imaging, and thermal infrared imaging, have significantly improved the efficiency of oil spill emergency response. However, these methods still have limitations. SAR is ineffective for close-range oil spill detection and has high requirements for surface water conditions, requiring suitable wind speeds and wave heights for effective identification. Multispectral imaging, which primarily uses the visible-to-near-infrared spectrum, has strict requirements for ambient lighting conditions and observation angles and can only be used during daylight hours. Thermal infrared imaging, which uses the temperature difference between surface oil and water for detection, can achieve all-day and all-weather detection, but identification is poor when the temperature difference is small. Consequently, existing surface oil spill monitoring technologies are unable to operate in harsh environmental conditions and suffer from a high false alarm rate.

[0004] Therefore, there is an urgent need for those skilled in the art to provide a sea surface oil spill detection device with greater reliability and higher detection imaging resolution capability. Summary of the Invention

[0005] The purpose of this application is to provide an underwater oil spill imaging detection method and equipment based on a polarization correlation algorithm, which improves the image quality of sea surface oil spill detection imaging and the reliability of sea surface oil spill detection.

[0006] To achieve the above objectives, this application provides the following solutions:

[0007] In a first aspect, the present application provides an underwater oil spill imaging detection method based on a polarization correlation algorithm, the underwater oil spill imaging detection method based on a polarization correlation algorithm comprising:

[0008] The laser signal is emitted to the sea surface area to be measured, and the horizontal polarization intensity and vertical polarization intensity of the reflected laser signal are collected; the sea surface area to be measured includes: the oil spill detection area and the background area;

[0009] Calculating a horizontally polarized polarization correlation image and a vertically polarized polarization correlation image based on the horizontally polarized light intensity and the vertically polarized light intensity of the reflected laser signal, respectively;

[0010] Obtaining a polarization image based on the horizontally polarized polarization correlation image and the vertically polarized polarization correlation image;

[0011] Based on the polarization image, the linear polarization degree of the oil spill detection area and the linear polarization degree of the background area are calculated;

[0012] Based on the horizontally polarized polarization correlation image, the vertically polarized polarization correlation image, the linear polarization degree of the oil spill detection area, and the linear polarization degree of the background area, the light intensity value of the reflected laser signal in the oil spill detection area is obtained;

[0013] Based on the linear polarization degree of the background area, the intensity of the background scattered light in the reflected laser signal is calculated;

[0014] Calculate the correction factor of the reflected laser signal in the oil spill detection area based on the horizontal polarization correlation image, the vertical polarization correlation image and the background scattered light intensity;

[0015] Determining a transmission function based on the horizontally polarized light intensity, the vertically polarized light intensity, the background scattered light intensity, the linear polarization degree of the background area, and the correction factor;

[0016] Based on the transmission function, the background scattered light intensity and the intensity value of the laser signal reflected in the oil spill detection area, a descattered restored image is determined, and the descattered restored image is used as an underwater oil spill imaging image.

[0017] Optionally, a calculation formula for the polarization correlation image of horizontal polarization is:

[0018] ;

[0019] in, Polarization correlation image representing horizontal polarization; represents the spatial distribution of the speckle field generated on the DMD for the kth time; Indicates the light intensity value in the horizontal polarization direction; represents the ensemble average;

[0020] The calculation formula of the polarization correlation image of vertical polarization is:

[0021] ;

[0022] in, Polarization-dependent image representing vertical polarization; Indicates the light intensity value in the vertical polarization direction.

[0023] Optionally, obtaining a polarization image based on the horizontally polarized polarization correlation image and the vertically polarized polarization correlation image specifically includes:

[0024] Take any pixel in the horizontally polarized polarization-correlated image as the current pixel, and for the current pixel:

[0025] Performing a pixel-by-pixel operation on the horizontal polarization degree of the current pixel and the vertical polarization degree of the corresponding pixel in the polarization correlation image of the vertical polarization to obtain the linear polarization degree of the current pixel;

[0026] Based on the linear polarization degrees of all pixel points, a polarization image including the linear polarization degrees of all pixel points is obtained.

[0027] Optionally, the calculation formula for determining the polarization image is:

[0028] ;

[0029] in, Represents a polarization image; Indicates the vertical polarization degree of the nth pixel; Indicates the horizontal polarization degree of the n-th pixel.

[0030] Optionally, the calculation formula for the light intensity value of the reflected laser signal in the oil spill detection area is:

[0031] ;

[0032] in, I obj Represents the light intensity of the laser signal after reflection in the oil spill detection area; P bg Represents the linear polarization degree of the background area; P ob Indicates the linear polarization degree of the oil spill detection area.

[0033] Optionally, based on the linear polarization degree of the background area, calculating the intensity of the background scattered light in the reflected laser signal specifically includes:

[0034] Calculate the difference in the intensity of the background scattered light in the horizontal polarization direction and the vertical polarization direction based on the intensity of the background scattered light in the horizontal polarization direction and the intensity of the background scattered light in the vertical polarization direction;

[0035] The intensity of the background scattered light in the reflected laser signal is determined based on the light intensity difference and the linear polarization degree of the background area.

[0036] Optionally, the calculation formula of the correction factor of the reflected laser signal in the oil spill detection area is:

[0037] ;

[0038] in, Represents the correction factor of the reflected laser signal in the oil spill detection area; Represents the intensity of the medium light in the parallel polarization state at infinity; Represents the intensity of the medium light with vertical polarization at infinity.

[0039] Optionally, determining the transmission function based on the horizontally polarized light intensity, the vertically polarized light intensity, the background scattered light intensity, the linear polarization degree of the background area, and the correction factor specifically includes:

[0040] Determine the difference value of polarization orthogonal image light intensity based on the horizontal polarization light intensity and the vertical polarization light intensity;

[0041] A weight coefficient is introduced, and the transfer function is determined based on the difference value of the polarization orthogonal image light intensity, the background scattered light intensity, the linear polarization degree of the background area and the correction factor.

[0042] Optionally, the calculation formula for determining the image after de-scattering restoration is:

[0043] ;

[0044] Where L(x,y) represents the image after de-scattering restoration; t (x,y) represents the transfer function; Indicates the intensity of background scattered light.

[0045] In a second aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the above-described methods for underwater oil spill imaging detection based on the polarization correlation algorithm.

[0046] According to the specific embodiments provided in this application, this application has the following technical effects:

[0047] The present application discloses an underwater oil spill imaging detection method and device based on a polarization correlation algorithm. By utilizing the horizontal and vertical polarization information of the reflected laser signal and combining it with a second-order correlation imaging algorithm, polarization correlation imaging is generated, which can significantly suppress underwater backscattering and improve the contrast and clarity of the image. By introducing a polarization correction factor, the influence of scattered light can be more accurately eliminated and the true polarization characteristics of the target can be restored, significantly improving the contrast of the imaging image. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0049] Figure 1 A schematic flow chart of an underwater oil spill imaging detection method based on a polarization correlation algorithm provided in one embodiment of the present application;

[0050] Figure 2 A schematic diagram of a data acquisition device provided in one embodiment of the present application;

[0051] Figure 3 A schematic diagram comparing the signal-to-noise ratios of a conventional underwater polarization imaging method provided in one embodiment of the present application and the polarization correlation imaging method of the present application under different turbidity conditions;

[0052] Figure 4 Schematic diagram of the change of signal-to-noise ratio under different turbidity conditions;

[0053] Figure 5 Schematic diagram of polarized images of underwater oil spills at different polarization angles provided by one embodiment of the present application; (a) is a polarized image of an underwater oil spill at a polarization angle of 0°, and (b) is an image of an underwater oil spill at a polarization angle of 90°;

[0054] Figure 6 This is a schematic diagram of an underwater oil spill image obtained based on the polarization correlation imaging method of this application;

[0055] Figure 7 This is a schematic diagram of an oil spill detection image after integrating the traditional underwater polarization imaging method with the polarization correlation imaging method of the present application;

[0056] Figure 8 A schematic diagram of the structure of a computer device provided in one embodiment of the present application.

[0057] Reference numerals:

[0058] Laser 1, collimating beam expander 2, digital micromirror device 3, polarization beam splitter 4, first barrel detector 5, second barrel detector 6, data processing unit 7. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0060] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0061] Compared with traditional remote sensing oil spill detection, underwater oil spill polarization correlation imaging detection has significant technical advantages. Remote sensing technologies such as synthetic aperture radar, multispectral imaging and thermal infrared imaging are often subject to environmental conditions and have high requirements for factors such as wind speed, wave height, and light. In addition, multispectral and infrared imaging are difficult to work effectively at night or in bad weather. At the same time, remote sensing technology mainly relies on single-dimensional optical data, such as spectral or polarization signals, which are easily interfered with by factors such as laser signals and waves reflected from the sea surface. In contrast, in order to avoid the problem of unsatisfactory resolution of oil spill detection imaging under harsh sea surface environments, this application can effectively suppress underwater backscattering and significantly improve the contrast and clarity of imaging by capturing horizontal and vertical polarization information and combining it with a second-order correlation imaging algorithm. It not only breaks through the limitations of traditional technologies in complex environments, but also realizes all-weather, high-contrast oil spill detection, and can realize oil spill detection imaging from the surface to the underwater, overcoming the problem of backscattering of underwater light transmission.

[0062] In an exemplary embodiment, Figure 1 As shown, a method for underwater oil spill imaging detection based on polarization correlation algorithm is provided, which includes the following steps.

[0063] Step S1, transmitting a laser signal to the sea surface area to be measured, and collecting the horizontal polarization intensity and vertical polarization intensity of the reflected laser signal; Figure 2 As shown, the sea surface area to be measured includes: an oil spill detection area and a background area.

[0064] Step S2 : calculating a horizontally polarized polarization correlation image and a vertically polarized polarization correlation image based on the horizontally polarized light intensity and the vertically polarized light intensity of the reflected laser signal, respectively.

[0065] As an optional implementation, in step S2, the calculation formula of the horizontal polarization correlation image is:

[0066] (1)

[0067] in, Polarization correlation image representing horizontal polarization; represents the spatial distribution of the speckle field generated on the DMD for the kth time; Indicates the light intensity value in the horizontal polarization direction; represents the ensemble average.

[0068] The calculation formula of the polarization correlation image of vertical polarization is:

[0069] (2)

[0070] in, Polarization-dependent image representing vertical polarization; Indicates the light intensity value in the vertical polarization direction.

[0071] Specifically, polarization correlation imaging is performed on the sea surface area to be measured, and the light intensity value in the horizontal polarization direction detected by the bucket detector is collected. and the light intensity in the vertical polarization direction , and substitute it into the second-order correlation imaging formula to obtain the horizontal polarization correlation image Polarization correlation image with vertical polarization .

[0072] Step S3 : obtaining a polarization image based on the horizontally polarized polarization correlation image and the vertically polarized polarization correlation image.

[0073] As an optional implementation, step S3 specifically includes:

[0074] Step S31: taking any pixel in the horizontally polarized polarization-correlated image as the current pixel, and performing the following operations on the current pixel:

[0075] Step S32 , performing a pixel-to-pixel operation on the horizontal polarization degree of the current pixel and the vertical polarization degree of the corresponding pixel in the vertical polarization correlation image to obtain the linear polarization degree of the current pixel.

[0076] Step S33 : obtaining a polarization image including the linear polarization degrees of all the pixels based on the linear polarization degrees of all the pixels.

[0077] As an optional implementation, the calculation formula for determining the polarization image is:

[0078] (3)

[0079] in, Represents a polarization image; Indicates the vertical polarization degree of the nth pixel; Indicates the horizontal polarization degree of the n-th pixel.

[0080] Specifically, in getting and Afterwards, extract M 11 (x, y) distribution. By performing calculations on each pixel of the horizontally polarized polarization correlation image and the vertically polarized polarization correlation image according to formula (3), the linear polarization degree distribution of each pixel in the field of view can be obtained. The physical meaning of formula (3) is to use the two images with different polarizations that have been obtained. and , performing pixel-by-pixel operations on the image will produce a polarized image , and the polarization image Represents the linear polarization distribution of the laser signal after reflection in the field of view.

[0081] In addition, polarization images It can also be calculated according to formula (4):

[0082] (4)

[0083] in, Represents the reflectivity distribution function; K is a constant term, and the polarization degree of the reflected laser signal is M 11 (x,y). According to the Stokes vector of the reflected laser signal (i.e., formula (5)) and the calculation formula of polarization degree DOP (i.e., formula (6)) are used to calculate the polarization degree of the reflected laser signal, i.e., M 11 (x,y). Among them,

[0084] (5)

[0085] (6)

[0086] in, Q Represents the light intensity difference between the horizontal polarization component and the vertical polarization component; U Indicates the intensity difference of polarization components in the ±45° direction; V represents the intensity difference between the right-hand polarization component and the left-hand polarization component; T represents the transpose of the matrix.

[0087] Step S4: Calculate the linear polarization degree of the oil spill detection area and the linear polarization degree of the background area based on the polarization image.

[0088] Specifically, on the basis of uniform object surface, Each point is the linear polarization value of the reflected light signal (i.e., the reflected laser signal) in the oil spill detection area or background area. Under the premise of being able to distinguish the outline of the oil spill target and the sea surface background, select the target area (i.e., the oil spill detection area or the background area) in the field of view and calculate the average value of the target area. The obtained target area average value is the linear polarization value of the target or background under the illumination of the linearly polarized light source. and .

[0089] The linear polarization degree of the oil spill detection area can be calculated by the following formula:

[0090] (7)

[0091] in, A tag Indicates an oil spill detection area.

[0092] The linear polarization degree of the corresponding background area can be calculated as follows:

[0093] (8)

[0094] in, A bg Indicates the background area.

[0095] Step S5 , obtaining the intensity value of the reflected laser signal in the oil spill detection area based on the horizontally polarized polarization correlation image, the vertically polarized polarization correlation image, the linear polarization degree of the oil spill detection area, and the linear polarization degree of the background area.

[0096] As an optional implementation, the calculation formula for the light intensity value of the reflected laser signal in the oil spill detection area is:

[0097] (9)

[0098] in, I obj Indicates the light intensity value of the laser signal after reflection in the oil spill detection area; P bg Indicates the linear polarization degree of the background area; P ob Indicates the degree of linear polarization in the oil spill detection area.

[0099] Step S6: Calculate the intensity of the background scattered light in the reflected laser signal based on the linear polarization degree of the background area.

[0100] As an optional implementation, step S6 specifically includes:

[0101] Step S61, calculating the difference in the intensity of the background scattered light in the horizontal polarization direction and the vertical polarization direction based on the intensity of the background scattered light in the horizontal polarization direction and the intensity of the background scattered light in the vertical polarization direction;

[0102] Step S62 : determining the intensity of the background scattered light in the reflected laser signal based on the light intensity difference and the linear polarization degree of the background area.

[0103] Background scattered light intensity A ∞ : Indicates that at infinity or in the background area, since the distance between the target object and the imaging device is infinite, the transmission function t(x,y) will approach zero (because light attenuates significantly during long-distance propagation). In this case, it can be approximately considered that the light intensity I(x,y) in the image is mainly composed of the background scattered light intensity A ∞ Therefore, it can be approximated by the following formula (10) and formula (11):

[0104] (10)

[0105] (11)

[0106] in, Indicates the intensity of background scattered light in the horizontal polarization direction; Indicates the intensity of background scattered light in the vertical polarization direction; Indicates the intensity difference of background scattered light in the horizontal and vertical polarization directions; It represents the functional relationship between the backscattered light intensity A∞ in the background area (i.e., infinitely far underwater) and the transmission function t(x,y); A quantitative representation of the difference between polarization orthogonal images.

[0107] Step S7 , calculating a correction factor of the reflected laser signal in the oil spill detection area based on the horizontally polarized polarization correlation image, the vertically polarized polarization correlation image, and the background scattered light intensity.

[0108] As an optional implementation, the calculation formula of the correction factor of the reflected laser signal in the oil spill detection area is:

[0109] (12)

[0110] in, Represents the correction factor of the reflected laser signal in the oil spill detection area; Represents the intensity of the medium light in the parallel polarization state at infinity; Represents the intensity of the medium light with vertical polarization at infinity.

[0111] The traditional underwater polarization imaging model assumes that the polarization degree of the reflected laser signal (i.e., the reflected laser signal in the oil spill detection area) can be ignored. However, in some cases, the polarization degree of the reflected laser signal may significantly affect the image quality. Therefore, the correction factor shown in formula (12) is introduced. The correction factor H(x,y) corrects the error caused by the polarization of the target light by normalizing the measured intensity difference of the correlation image to the intensity difference of the medium at infinity.

[0112] Step S8, determining a transfer function based on the horizontally polarized light intensity, the vertically polarized light intensity, the background scattered light intensity, the linear polarization degree of the background area, and the correction factor;

[0113] As an optional implementation, step S8 specifically includes:

[0114] Step S81 : determining a difference value of polarized orthogonal image light intensities based on the horizontally polarized light intensities and the vertically polarized light intensities.

[0115] Step S82 , introducing a weight coefficient, and determining the transfer function based on the difference value of the polarization orthogonal image light intensity, the background scattered light intensity, the linear polarization degree of the background area, and the correction factor.

[0116] Specifically, by normalizing the measured correlation image intensity difference (i.e., the difference in polarization orthogonal image intensity) to the medium intensity difference at infinity, the error caused by the polarization degree of the reflected laser signal is corrected, especially when the polarization degree of the reflected laser signal cannot be ignored. In this way, the transfer function t(x,y) can be adjusted by H(x,y) to improve the effect of descattering imaging. At the same time, the weight coefficient is introduced. (0< <1), can be adjusted The influence on the transfer function t(x,y) is as follows:

[0117] (13)

[0118] in, Represents the difference in polarization orthogonal image intensity, specifically the difference between the parallel polarization intensity and the perpendicular polarization intensity; Indicates the scattered light intensity at infinity (i.e., the background scattered light intensity); The degree of linear polarization of the background area; Represents the polarization correction factor of the reflected laser signal.

[0119] Step S9: determining a descattered restored image based on the transfer function, the background scattered light intensity, and the intensity of the laser signal reflected in the oil spill detection area, and using the descattered restored image as the underwater oil spill imaging image.

[0120] Specifically, the de-scattered restored image is determined by combining the polarization correlation imaging model with the traditional underwater polarization imaging model, and the de-scattered restored image is used as the underwater oil spill imaging image. , see Equations (14) and (15). The intensity of the laser signal L(x, y) actually reflected by the target object and then scattered and absorbed by the medium with a transmission function of t(x, y) is O(x, y). B(x, y) is the intensity of the backscattered light A at infinity underwater (i.e., the background). ∞ This process ensures that the imaging result can more realistically reflect the target image while eliminating backscattered light and noise interference.

[0121] (14)

[0122] (15)

[0123] Where L(x,y) represents the image after de-scattering restoration; t (x,y) represents the transfer function.

[0124] Furthermore, a schematic diagram comparing the SNR of the polarization correlation imaging generated by the conventional underwater polarization imaging and the underwater oil spill imaging detection method based on the polarization correlation algorithm of the present application (hereinafter referred to as the polarization correlation imaging method of the present application) is shown in FIG. Figure 3 As shown, Figure 3 A comparison of the signal-to-noise ratio (SNR) between the traditional underwater polarization imaging method and the polarization correlation imaging method of the present application under different turbidity conditions is demonstrated. It can be seen that under low turbidity conditions (such as below 20 NTU), the traditional underwater polarization imaging can provide better imaging effects and a higher signal-to-noise ratio due to the weak scattering effect; as the turbidity of the water body gradually increases, especially in high turbidity environments (such as above 30 NTU), the polarization correlation imaging of the present application can better suppress backscattered light, so the signal-to-noise ratio gradually improves and surpasses the traditional underwater polarization imaging, becoming a dominant method for imaging in complex environments. Figure 3 The performance of the two imaging methods under different turbidity conditions is intuitively demonstrated. When the turbidity is low, traditional underwater polarization imaging works better; when the turbidity is high, the polarization correlation imaging of this application can better improve image quality and provide a higher signal-to-noise ratio.

[0125] Figure 4The figure shows how the signal-to-noise ratio (SNR) changes with increasing iterations under different turbidity conditions (20 NTU, 30 NTU, 40 NTU, etc.). It can be observed that the SNR improves across all turbidity conditions with increasing iterations, indicating that imaging quality improves significantly with more iterations.

[0126] Figure 5 Schematic diagram of polarization images of underwater oil spills at different polarization angles. Figure 5 (a) shows the polarization image of the underwater oil spill at a polarization angle of 0°, which clearly shows the reflection characteristics of the oil spill area at a polarization angle of 0°; Figure 5 (b) shows an underwater oil spill image at a 90° polarization angle, where the polarization information of the oil spill outline is more prominent.

[0127] Figure 6 and Figure 7 The following images illustrate the imaging results of our proposed underwater oil spill imaging method based on the polarization correlation algorithm, demonstrating the effectiveness of different imaging methods in underwater oil spill detection. This comparative analysis clearly demonstrates the differences between our proposed polarization correlation imaging method and traditional underwater polarization imaging methods, as well as the resulting optimization effects of combining them.

[0128] Figure 6 The underwater oil spill image obtained by the polarization correlation imaging method of the present application is presented. The image is obtained by collecting horizontal polarized light intensity I ∥ and vertically polarized light intensity I ⊥ , combined with a second-order polarization correlation algorithm, effectively suppresses scattered light in the underwater environment, making the boundaries and outlines of the oil spill area clearer. Specifically: the black and white contrast of the image is more significant, forming a sharp contrast between the oil spill area and the background water, making the edge features of the oil spill clearly stand out. Compared with traditional underwater polarization imaging methods, the polarization correlation imaging method of this application can more effectively eliminate the influence of scattered light, presenting a more realistic and clear oil spill outline.

[0129] Figure 7 The oil spill detection image after the fusion of the traditional underwater polarization imaging method and the polarization correlation imaging method of the present application is shown. This method generates a more accurate oil spill image by combining the advantages of the underwater polarization imaging method and the anti-scattering ability of the polarization correlation imaging of the present application. The specific effects include: Figure 6 In comparison, the fusion method makes the oil spill boundary more natural and has a certain transition effect. This improvement may be due to the introduction of traditional imaging technology, which allows the image to retain more background information while removing scattering. Through fusion processing, the brightness of the image is enhanced, the intensity of the reflected laser signal in the oil spill area is significantly improved, and the overall imaging quality is further improved.

[0130] Comparing these two images clearly demonstrates the effectiveness of different imaging technologies in underwater oil spill detection. The polarization correlation imaging method used in this application demonstrates significant advantages in removing scattered light, and its combination with traditional imaging methods further enhances imaging performance, providing a more accurate solution for underwater oil spill detection.

[0131] Furthermore, Figure 2 Schematic diagram of a data acquisition device for underwater oil spill imaging detection based on polarization correlation algorithm, where:

[0132] Laser 1 is used to emit a laser beam with a wavelength of 532nm as a light source for underwater oil spill detection.

[0133] The collimating beam expander 2 is used to collimate the laser beam emitted from the laser, so that the laser beam remains parallel, ensuring that it can maintain high precision during underwater transmission.

[0134] The Digital Micromirror Device (DMD) 3 receives the speckle field sent by the data processing unit to control the light field of the light beam, ensuring that the laser can accurately scan the oil spill area.

[0135] The polarization beam splitter (PBS) 4 is used to split the laser beam modulated by the DMD into two beams with different polarization states, so as to distinguish the polarization information of the oil spill area.

[0136] The first and second detectors, 5 and 6, respectively receive the two light beams with different polarization states after being split by the PBS, acquiring polarization imaging data of the underwater oil spill. The first and second detectors, 5 and 6, convert the received optical signals into electrical signals for subsequent analysis and processing.

[0137] The data processing unit 7 is connected to the first barrel detector 5, the second barrel detector 6 and the digital micromirror device 3, and is used to randomly generate a reference speckle pattern and send it to the digital micromirror device 3, receive the electrical signal transmitted by the first barrel detector 5 or the second barrel detector 6, perform correlation imaging calculation using the underwater oil spill imaging detection method based on the polarization correlation algorithm of the present application, and finally generate an underwater oil spill imaging image.

[0138] (1) This application combines the polarization correlation imaging model with the traditional underwater polarization imaging model, breaking through the limitations of traditional technologies in dealing with the effects of scattered light in complex underwater environments. Polarization correlation imaging utilizes the horizontal and vertical polarization information of the reflected laser signal, combined with the second-order correlation imaging algorithm, to significantly suppress underwater backscattering and improve image contrast and clarity.

[0139] (2) By introducing the polarization correction factor H(x,y), this application can more accurately eliminate the influence of scattered light and restore the true polarization characteristics of the target object, thereby improving the overall performance of the imaging system. In complex underwater scenes, this innovative method not only solves the problem of low efficiency of traditional models in processing backscattered light in complex underwater environments, but also can more accurately correct the polarization information of the reflected laser signal and better restore the reflected laser signal of the underwater target object, thereby improving the imaging quality.

[0140] (3) This application introduces the correction factor H(x,y) into the traditional polarization imaging model. By adjusting the normalized light intensity difference, optimizing the transfer function, and combining it with an adjustable weight coefficient, it flexibly adapts to different imaging conditions and effectively improves the descattering effect during the imaging process. This method is particularly suitable for complex underwater environments, especially when the polarization degree of the laser signal after the reflection of oil spills on the sea surface has a significant impact on the imaging quality, and can significantly improve the image contrast. The signal-to-noise ratio of this polarization correlation algorithm is improved by 30% compared to traditional polarization imaging.

[0141] In an exemplary embodiment, a computer device is provided, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement an underwater oil spill imaging detection method based on a polarization correlation algorithm.

[0142] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for underwater oil spill imaging detection based on a polarization correlation algorithm is implemented.

[0143] Those skilled in the art will understand that Figure 8The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0144] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0145] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0146] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0147] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0148] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. An underwater oil spill imaging detection method based on polarization correlation algorithm, characterized in that: The underwater oil spill imaging detection method based on the polarization correlation algorithm includes: The laser signal is emitted to the sea surface area to be measured, and the horizontal polarization intensity and vertical polarization intensity of the reflected laser signal are collected; the sea surface area to be measured includes: the oil spill detection area and the background area; Calculating a horizontally polarized polarization correlation image and a vertically polarized polarization correlation image based on the horizontally polarized light intensity and the vertically polarized light intensity of the reflected laser signal, respectively; Obtaining a polarization image based on the horizontally polarized polarization correlation image and the vertically polarized polarization correlation image; Based on the polarization image, the linear polarization degree of the oil spill detection area and the linear polarization degree of the background area are calculated. This requires that the object surface is uniform and the contours of the oil spill target and the background can be distinguished. Based on the horizontally polarized polarization correlation image, the vertically polarized polarization correlation image, the linear polarization degree of the oil spill detection area, and the linear polarization degree of the background area, the light intensity value of the reflected laser signal in the oil spill detection area is obtained; Based on the linear polarization degree of the background area, the intensity of the background scattered light in the reflected laser signal is calculated; Based on the horizontal polarization correlation image, the vertical polarization correlation image, and the background scattered light intensity, the correction factor of the laser signal after reflection in the oil spill detection area is calculated. The calculation formula of the correction factor of the laser signal after reflection in the oil spill detection area is: ； in, Represents the correction factor of the reflected laser signal in the oil spill detection area; Represents the intensity of the medium light in the parallel polarization state at infinity; Represents the intensity of the medium light in the vertical polarization state at infinity; Indicates the vertical polarization degree of the nth pixel; Indicates the horizontal polarization degree of the nth pixel; Determining a transmission function based on the horizontally polarized light intensity, the vertically polarized light intensity, the background scattered light intensity, the linear polarization degree of the background area, and the correction factor; Based on the transmission function, the background scattered light intensity and the intensity value of the laser signal reflected in the oil spill detection area, a descattered restored image is determined, and the descattered restored image is used as an underwater oil spill imaging image.

2. The underwater oil spill imaging detection method based on polarization correlation algorithm according to claim 1 is characterized in that: The calculation formula of the polarization correlation image of horizontal polarization is: ； in, Polarization correlation image representing horizontal polarization; represents the spatial distribution of the speckle field generated on the DMD for the kth time; Indicates the light intensity value in the horizontal polarization direction; represents the ensemble average; The calculation formula of the polarization correlation image of vertical polarization is: ； in, Polarization-dependent image representing vertical polarization; Indicates the light intensity value in the vertical polarization direction.

3. The underwater oil spill imaging detection method based on polarization correlation algorithm according to claim 1 is characterized in that: Obtaining a polarization image based on the horizontally polarized polarization correlation image and the vertically polarized polarization correlation image specifically includes: Take any pixel in the horizontally polarized polarization-correlated image as the current pixel, and for the current pixel: Performing a pixel-by-pixel operation on the horizontal polarization degree of the current pixel and the vertical polarization degree of the corresponding pixel in the polarization correlation image of the vertical polarization to obtain the linear polarization degree of the current pixel; Based on the linear polarization degrees of all pixel points, a polarization image including the linear polarization degrees of all pixel points is obtained.

4. The underwater oil spill imaging detection method based on polarization correlation algorithm according to claim 3 is characterized in that: The calculation formula for determining the polarization image is: ； in, Represents a polarization image.

5. The underwater oil spill imaging detection method based on polarization correlation algorithm according to claim 4 is characterized in that: The calculation formula for the light intensity of the reflected laser signal in the oil spill detection area is: ； in, I obj Represents the light intensity of the laser signal after reflection in the oil spill detection area; P bg Represents the linear polarization degree of the background area; P ob Indicates the degree of linear polarization in the oil spill detection area.

6. The underwater oil spill imaging detection method based on polarization correlation algorithm according to claim 5 is characterized in that: Based on the linear polarization degree of the background area, the intensity of the background scattered light in the reflected laser signal is calculated, specifically including: Calculate the difference in the intensity of the background scattered light in the horizontal polarization direction and the vertical polarization direction based on the intensity of the background scattered light in the horizontal polarization direction and the intensity of the background scattered light in the vertical polarization direction; The intensity of the background scattered light in the reflected laser signal is determined based on the light intensity difference and the linear polarization degree of the background area.

7. The underwater oil spill imaging detection method based on polarization correlation algorithm according to claim 6 is characterized in that: Determining a transmission function based on the horizontally polarized light intensity, the vertically polarized light intensity, the background scattered light intensity, the linear polarization degree of the background area, and the correction factor specifically includes: Determine the difference value of polarization orthogonal image light intensity based on the horizontal polarization light intensity and the vertical polarization light intensity; A weight coefficient is introduced, and the transfer function is determined based on the difference value of the polarization orthogonal image light intensity, the background scattered light intensity, the linear polarization degree of the background area and the correction factor.

8. The underwater oil spill imaging detection method based on polarization correlation algorithm according to claim 7 is characterized in that: The calculation formula for determining the image after de-scattering restoration is: ； Where L(x,y) represents the image after de-scattering restoration; t (x,y) represents the transfer function; Indicates the intensity of background scattered light.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and runnable on the processor, characterized in that the processor executes the computer program to implement the underwater oil spill imaging detection method based on the polarization correlation algorithm according to any one of claims 1 to 8.

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