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

Abstract

The invention discloses an underwater oil spill imaging detection method and device based on a polarization correlation algorithm, and relates to the technical field of underwater target detection imaging, and the method comprises the steps: calculating a polarization correlation image based on the horizontal polarized light intensity and the vertical polarized light intensity of a reflected laser signal; obtaining a polarization image based on the polarization correlation image, and calculating linear polarization degrees of different areas; based on the polarization correlation image and the linear polarization degree of the oil spill detection area and the background area, the light intensity value of the reflected laser signal and the light intensity of background scattered light are obtained; calculating a correction factor of the reflected laser signal based on the polarization correlation image and the background scattered light intensity; determining a transmission function based on the polarized light intensity, the background scattered light intensity, the linear polarization degree of the background area and the correction factor; and based on the transmission function, the light intensity of the background scattered light and the light intensity value of the reflected laser signal, determining an image after scattering removal and restoration. According to the invention, the image quality and reliability of sea surface oil spill detection imaging are improved.

Description

Technical Field

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

[0002] An oil spill is a maritime emergency that occurs during offshore oil exploration, development, and transportation due to accidental accidents or operational errors, resulting in the leakage of crude oil or oil products. With the rapid development of the economy, China's demand for oil energy is increasing continuously. The activities of offshore oil resource development, transportation, and storage are increasing day by day, and the risk of offshore oil spill accidents is increasing day by day. China is a major crude oil importer. According to statistics, 90% of its crude oil is transported by sea. Marine oil spills are the most typical and serious environmental pollution accidents in the process of human exploration of the ocean. Once they occur, the resulting pollution is very destructive to the marine environment and marine biological resources. If the oil film is washed to the shore by the wind and waves, it will also pollute the shoreline and tidal flats, damage the aquaculture industry, affect the coastal tourism industry, and threaten human health.

[0003] During the process of offshore oil production operations, offshore oil spills are major risk points in terms of safety and environmental protection in daily production management. If early detection and warning can be achieved, early discovery and treatment can be carried out, thereby reducing pollution to the marine environment and corresponding economic losses. With the progress of remote sensing technology, technologies such as synthetic aperture radar, multi-spectral imaging, and thermal infrared imaging have greatly promoted the efficiency of oil spill emergency response. However, the above methods still have limitations. The synthetic aperture radar method has poor detection effects on near-distance oil spills and requires relatively high water surface environmental conditions. More appropriate wind speeds and wave heights are required to obtain better recognition effects. Multi-spectral imaging mainly uses the spectra in the visible-near infrared spectral band for imaging, requires relatively high environmental light conditions and observation angles, and can only be used during the day. The thermal infrared imaging method uses the temperature difference between the floating oil on the water surface and the water for detection, and can achieve all-day and all-weather detection. However, when the temperature difference is small, the recognition effect is poor. Therefore, it can be seen that the existing offshore oil spill monitoring technologies cannot be implemented under harsh environmental conditions, and the monitoring false alarm rate is relatively high.

[0004] Therefore, it is urgent for those skilled in the art to provide an offshore oil spill detection device with stronger reliability and higher detection imaging resolution ability. Summary of the Invention

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

[0006] To achieve the above purpose, the present application provides the following solutions: 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 the polarization correlation algorithm includes: Emitting a laser signal to the sea area to be measured, and collecting the horizontal polarization intensity and vertical polarization intensity of the reflected laser signal; the sea area to be measured includes: an oil spill detection area and a background area; Based on the horizontal polarization intensity and vertical polarization intensity of the reflected laser signal respectively, calculating a polarization correlation image of horizontal polarization and a polarization correlation image of vertical polarization; Based on the polarization correlation image of horizontal polarization and the polarization correlation image of vertical polarization, obtaining a polarization image; Based on the polarization image, calculating the degree of linear polarization of the oil spill detection area and the degree of linear polarization of the background area; Based on the polarization correlation image of horizontal polarization, the polarization correlation image of vertical polarization, the degree of linear polarization of the oil spill detection area, and the degree of linear polarization of the background area, obtaining the intensity value of the reflected laser signal in the oil spill detection area; Based on the degree of linear polarization of the background area, calculating the intensity of the background scattered light in the reflected laser signal; Based on the polarization correlation image of horizontal polarization, the polarization correlation image of vertical polarization, and the intensity of the background scattered light, calculating a correction factor for the reflected laser signal in the oil spill detection area; Based on the horizontal polarization intensity, the vertical polarization intensity, the intensity of the background scattered light, the degree of linear polarization of the background area, and the correction factor, determining a transfer function; Based on the transfer function, the intensity of the background scattered light, and the intensity value of the reflected laser signal in the oil spill detection area, determining a de-scattered and restored image, and using the de-scattered and restored image as an underwater oil spill imaging image.

[0007] Optionally, the calculation formula for the polarization correlation image of horizontal polarization is: ; Wherein, represents the polarization correlation image of horizontal polarization; represents the spatial distribution of the k-th generated speckle field on the DMD; represents the intensity value in the horizontal polarization direction; represents the ensemble average; The calculation formula for the polarization correlation image of vertical polarization is: ; Wherein, represents the polarization correlation image of horizontal polarization; represents the intensity value in the vertical polarization direction.

[0008] Optionally, based on the polarization correlation image of horizontal polarization and the polarization correlation image of vertical polarization, a polarization image is obtained, specifically including: Taking any pixel point in the polarization correlation image of horizontal polarization as the current pixel point, for the current pixel point: Performing pixel-by-pixel operation on the horizontal polarization degree of the current pixel point and the vertical polarization degree of the corresponding pixel point in the polarization correlation image of vertical polarization to obtain the linear polarization degree of the current pixel point; Based on the linear polarization degrees of all pixel points, a polarization image including the linear polarization degrees of all pixel points is obtained.

[0009] Optionally, the calculation formula for determining the polarization image is: ; Wherein, represents the polarization image; represents the horizontal polarization degree of the nth pixel point; represents the vertical polarization degree of the nth pixel point.

[0010] Optionally, the calculation formula for the light intensity value of the reflected laser signal in the oil spill detection area is: ; Wherein, I obj represents the light intensity value of the reflected laser signal in the oil spill detection area; P bg represents the linear polarization degree of the background area; P ob represents the linear polarization degree of the oil spill detection area.

[0011] Optionally, based on the linear polarization degree of the background area, calculating the background scattered light intensity in the reflected laser signal specifically includes: Calculating the light intensity difference between the background scattered light in the horizontal polarization direction and the vertical polarization direction based on the light intensity of the background scattered light in the horizontal polarization direction and the vertical polarization direction; Determining the background scattered light intensity in the reflected laser signal based on the light intensity difference and the linear polarization degree of the background area.

[0012] Optionally, the calculation formula for the correction factor of the reflected laser signal in the oil spill detection area is: ; Wherein, represents the correction factor of the reflected laser signal in the oil spill detection area; represents the medium light intensity of the parallel polarization state at infinity; represents the medium light intensity of the vertical polarization state at infinity.

[0013] Optionally, based on the horizontal polarization light intensity, vertical polarization light intensity, background scattered light intensity, linear polarization degree of the background region, and the correction factor, a transmission function is determined, specifically including: Based on the horizontal polarization light intensity and the vertical polarization light intensity, a difference value of the polarization orthogonal image light intensity is determined; A weight coefficient is introduced, and based on the difference value of the polarization orthogonal image light intensity, the background scattered light intensity, the linear polarization degree of the background region, and the correction factor, the transmission function is determined.

[0014] Optionally, the calculation formula for determining the image after de-scattering restoration is: ; wherein, L(x, y) represents the image after de-scattering restoration; t (x, y) represents the transmission function.

[0015] In a second aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the underwater oil spill imaging detection method based on the polarization correlation algorithm described in any one of the above.

[0016] According to the specific embodiments provided by the present application, the present application has the following technical effects: 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 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 degree 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

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required to be used in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0018] Figure 1 It is a schematic flowchart of an underwater oil spill imaging detection method based on a polarization correlation algorithm provided by an embodiment of the present application; Figure 2 It is a schematic diagram of a data acquisition device provided by an embodiment of the present application; Figure 3Schematic diagram of the signal-to-noise ratio comparison between the traditional underwater polarization imaging method and the polarization correlation imaging method of the present application under different turbidity conditions; Figure 4 Schematic diagram of the change of the signal-to-noise ratio under different turbidity conditions; Figure 5 Schematic diagram of the underwater oil spill polarization images at different polarization angles provided by an embodiment of the present application; among them, (a) is the underwater oil spill polarization image at a polarization angle of 0°, and (b) is the underwater oil spill image at a polarization angle of 90°; Figure 6 Schematic diagram of the underwater oil spill image obtained by the polarization correlation imaging method of the present application; Figure 7 Schematic diagram of the oil spill detection image after fusing the traditional underwater polarization imaging method and the polarization correlation imaging method of the present application; Figure 8 Schematic diagram of the structure of a computer device provided by an embodiment of the present application.

[0019] Reference numerals: Laser 1, collimating and beam expanding mirror 2, digital micromirror device 3, polarization beam splitter 4, first bucket detector 5, second bucket detector 6, data processing unit 7. Detailed implementation manners

[0020] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0021] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below in conjunction with the drawings and specific implementation manners.

[0022] 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, multi-spectral imaging, and thermal infrared imaging are often restricted by environmental conditions, have high requirements for factors such as wind speed, wave height, and lighting, and multi-spectral and infrared imaging are difficult to work effectively at night or in bad weather. At the same time, remote sensing technologies mainly rely on single-dimensional optical data, such as spectral or polarization signals, and are easily interfered by factors such as laser signals and waves after sea surface reflection. In contrast, in order to avoid the problem of unsatisfactory imaging resolution in oil spill detection under harsh sea surface environments, this application can effectively suppress underwater backscattering by capturing horizontal and vertical polarization information and combining the second-order correlation imaging algorithm, significantly improving the contrast and clarity of imaging. It not only breaks through the limitations of traditional technologies in complex environments but also realizes all-weather and high-contrast oil spill detection, enabling oil spill detection imaging from the water surface to underwater and overcoming the problem of backscattering of underwater light transmission.

[0023] In an exemplary embodiment, as Figure 1 shown, a method for underwater oil spill imaging detection based on a polarization correlation algorithm is provided, including the following steps. Among them: Step S1, emit a laser signal to the sea area to be measured, and collect the horizontal polarization intensity and vertical polarization intensity of the reflected laser signal; as Figure 2 shown, the sea area to be measured includes: an oil spill detection area and a background area.

[0024] Step S2, respectively calculate the polarization correlation image of horizontal polarization and the polarization correlation image of vertical polarization based on the horizontal polarization intensity and vertical polarization intensity of the reflected laser signal.

[0025] As an optional implementation manner, in step S2, the calculation formula for the polarization correlation image of horizontal polarization is: (1) Wherein, represents the polarization correlation image of horizontal polarization; represents the spatial distribution of the k-th generated speckle field on the DMD; represents the light intensity value in the horizontal polarization direction; represents the ensemble average.

[0026] The calculation formula for the polarization correlation image of vertical polarization is: (2) Wherein, represents the polarization correlation image of horizontal polarization; represents the light intensity value in the vertical polarization direction.

[0027] Specifically, perform polarization correlation imaging on the sea area to be measured respectively, and collect the light intensity values in the horizontal polarization direction detected by the bucket detector and the light intensity values in the vertical polarization direction , substitute them into the second-order correlation imaging formula to obtain the polarization correlation image of horizontal polarization and the polarization correlation image of vertical polarization .

[0028] Step S3, based on the polarization correlation image of horizontal polarization and the polarization correlation image of vertical polarization, obtain a polarization image

[0029] As an alternative implementation, step S3 specifically includes: Step S31, take any pixel point in the polarization correlation image of horizontal polarization as the current pixel point. For the current pixel point: Step S32, perform pixel-by-pixel operation on the horizontal polarization degree of the current pixel point and the vertical polarization degree of the corresponding pixel point in the polarization correlation image of vertical polarization to obtain the linear polarization degree of the current pixel point

[0030] Step S33, based on the linear polarization degrees of all pixel points, obtain a polarization image containing the linear polarization degrees of all pixel points

[0031] As an alternative implementation, the calculation formula for determining the polarization image is: (3) wherein, represents the polarization image; represents the horizontal polarization degree of the nth pixel point; represents the vertical polarization degree of the nth pixel point

[0032] Specifically, after obtaining and , extract the distribution of M 11 (x,y). Perform the operation on each pixel point of the polarization correlation image of horizontal polarization and the polarization correlation image of vertical polarization according to formula (3), and the linear polarization degree distribution of each pixel point in the field of view can be obtained. The physical meaning of formula (3) is to utilize the two obtained images with polarization differences and , perform pixel-by-pixel operation processing on the images to obtain the polarization image , and the polarization image represents the linear polarization degree distribution of the reflected laser signal in the field of view

[0033] In addition, the polarization image can also be calculated according to formula (4): (4) Among them, represents the reflectivity distribution function; K is a constant term, and the degree of polarization of the reflected laser signal is M 11 (x, y). According to the Stokes vector of the reflected laser signal (i.e., Equation (5)) and the calculation formula of the degree of polarization DOP (i.e., Equation (6)), calculate the degree of polarization of the reflected laser signal, that is, M 11 (x, y). Among them, (5) (6) Among them, Q represents the light intensity difference between the horizontally polarized component and the vertically polarized component; U represents the light intensity difference between the polarization components in the ±45° direction; V represents the light intensity difference between the right-handed polarized component and the left-handed polarized component; T represents the transpose of the matrix.

[0034] Step S4, based on the polarization image, calculate the linear polarization degree of the oil spill detection area and the linear polarization degree of the background area.

[0035] Specifically, on the basis of a uniform object surface, each point in is the linear polarization degree value of the reflected light signal (i.e., the reflected laser signal) of the oil spill detection area or the background area. On the premise that the oil spill target on the sea surface and the sea surface background contour can be distinguished, select the target area (i.e., the oil spill detection area or the background area) in the field of view and average the target area, and the obtained target area average value is the linear polarization degree value of the target or the background under the illumination of the linear polarization light source and .

[0036] The linear polarization degree of the oil spill detection area can be calculated by the following formula: (7) Among them, A tag represents the oil spill detection area.

[0037] The corresponding linear polarization degree of the background area can be calculated by the following formula: (8) Among them, A bg represents the background area.

[0038] Step S5, based on the polarization correlation image of horizontal polarization, the polarization correlation image of vertical polarization, the linear polarization degree of the oil spill detection area, and the linear polarization degree of the background area, obtain the light intensity value of the reflected laser signal in the oil spill detection area.

[0039] As an alternative implementation, the calculation formula for the light intensity value of the reflected laser signal in the oil spill detection area is: (9) Wherein, I obj represents the light intensity value of the reflected laser signal in the oil spill detection area; P bg represents the degree of linear polarization of the background area; P ob represents the degree of linear polarization of the oil spill detection area.

[0040] Step S6, based on the degree of linear polarization of the background area, calculate the light intensity of the background scattered light in the reflected laser signal.

[0041] As an alternative implementation, step S6 specifically includes: Step S61, based on the light intensity of the background scattered light in the horizontal polarization direction and the light intensity in the vertical polarization direction, calculate the light intensity difference of the background scattered light in the horizontal polarization direction and the vertical polarization direction; Step S62, based on the light intensity difference and the degree of linear polarization of the background area, determine the light intensity of the background scattered light in the reflected laser signal.

[0042] Light intensity A of background scattered light ∞ : It means that at infinity or in the background area, due to the infinite distance between the target object and the imaging device, the transfer 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 contributed by the light intensity A of the background scattered light ∞ Therefore, it can be approximately obtained through the following formulas (10) and (11): (10) (11) Wherein, represents the light intensity of the background scattered light in the horizontal polarization direction; represents the light intensity of the background scattered light in the vertical polarization direction; represents the light intensity difference of the background scattered light in the horizontal and vertical polarization directions; represents the functional relationship between the backscattered light intensity A∞ of the background area (i.e., infinity underwater) and the transfer function t(x,y); represents the quantitative representation of the difference between polarization orthogonal images.

[0043] Step S7, based on the polarization correlation image of horizontal polarization, the polarization correlation image of vertical polarization, and the light intensity of the background scattered light, calculate the correction factor of the reflected laser signal in the oil spill detection area.

[0044] As an alternative implementation, the calculation formula for the correction factor of the reflected laser signal in the oil spill detection area is: (12) Wherein, represents the correction factor of the reflected laser signal in the oil spill detection area; represents the medium light intensity of the parallel polarization state at infinity; represents the medium light intensity of the vertical polarization state at infinity.

[0045] 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) normalizes the measured correlation image light intensity difference to the medium light intensity difference at infinity, and corrects the error caused by the influence of the target light polarization degree.

[0046] Step S8, determine the transfer function based on the horizontal polarization light intensity, vertical polarization light intensity, background scattered light intensity, linear polarization degree of the background area, and the correction factor; As an alternative implementation, step S8 specifically includes: Step S81, determine the difference value of the polarization orthogonal image light intensity based on the horizontal polarization light intensity and the vertical polarization light intensity.

[0047] Step S82, introduce a weight coefficient, and determine 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.

[0048] Specifically, by normalizing the measured correlation image light intensity difference (i.e., the difference value of the polarization orthogonal image light intensity) to the medium light intensity difference at infinity, the error caused by the influence of 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 de-scattering imaging. At the same time, a weight coefficient is introduced (0 < < 1), which can adjust the influence on the transfer function t(x, y), and the expression of the transfer function is: (13) Wherein, represents the difference of the polarization orthogonal image light intensity, specifically the difference between the parallel polarization light intensity and the vertical polarization light intensity; represents the scattered light intensity at infinity (i.e., the background scattered light intensity); Degree of linear polarization of the background region; represents the polarization correction factor of the laser signal after reflection.

[0049] Step S9, based on the transfer function, the background scattered light intensity, and the light intensity value of the reflected laser signal in the oil spill detection area, determine the image after de-scattering restoration, and use the image after de-scattering restoration as the underwater oil spill imaging image.

[0050] Specifically, determine the image after de-scattering restoration by combining the polarization correlation imaging model with the traditional underwater polarization imaging model, and use the image after de-scattering restoration as the underwater oil spill imaging image , referring to Equation (14) and Equation (15), the light intensity O(x, y) that reaches the detector after the laser signal L(x, y) actually reflected by the target object is scattered and absorbed by the medium with the transfer function t(x, y); B(x, y) is the backscattered light intensity A at infinity underwater (i.e., the background) ∞ and a function of the transfer function t(x, y). This process ensures that the imaging result can more truly reflect the target image on the basis of eliminating the backscattered light and noise interference.

[0051] (14) (15) where L(x, y) represents the image after de-scattering restoration; t (x, y) represents the transfer function.

[0052] Furthermore, the schematic diagram of the SNR comparison of the polarization correlation imaging generated by the traditional underwater polarization imaging and the underwater oil spill imaging detection method based on the polarization correlation algorithm in this application (hereinafter referred to as the polarization correlation imaging method in this application) is as Figure 3 shown, Figure 3 It shows the SNR comparison between the traditional underwater polarization imaging method and the polarization correlation imaging method in this application under different turbidity conditions. It can be seen that at low turbidity (below 20 NTU), due to the weak scattering effect, the traditional underwater polarization imaging can provide better imaging results and a higher SNR; as the water turbidity gradually increases, especially in a high turbidity environment (above 30 NTU), the polarization correlation imaging in this application can better suppress the backscattered light, so the SNR gradually increases and exceeds the traditional underwater polarization imaging, becoming an advantageous method for imaging in complex environments. Figure 3Intuitively illustrates the performance of two imaging methods under different turbidity conditions. When the turbidity is low, the traditional underwater polarization imaging has a better effect; when the turbidity is high, the polarization correlation imaging of the present application can better improve the image quality and provide a higher signal-to-noise ratio.

[0053] Figure 4 Shows the variation of the signal-to-noise ratio (SNR) with the increase in the number of computational iterations under different turbidity conditions (20 NTU, 30 NTU, 40 NTU, etc.). It can be observed that as the number of iterations increases, the SNR under all turbidity conditions gradually increases, indicating that the imaging quality has been significantly improved through more iterative calculations.

[0054] Figure 5 Is a schematic diagram of the underwater oil spill polarization image at different polarization angles. Figure 5 In (a) shows the underwater oil spill polarization image at a polarization angle of 0°, which clearly demonstrates the reflection characteristics of the oil spill area at a polarization angle of 0°; Figure 5 In (b) shows the underwater oil spill image at a polarization angle of 90°, and the polarization information of the oil spill contour is more significant.

[0055] Figure 6 and Figure 7 Are the imaging effect diagrams of the underwater oil spill imaging detection method based on the polarization correlation algorithm of the present application, respectively showing the application effects of different imaging methods in underwater oil spill detection. Through comparative analysis, it can be clearly seen the differences between the polarization correlation imaging of the present application and the traditional underwater polarization imaging method and the optimization effect produced by their combination.

[0056] Figure 6 Displays the underwater oil spill image obtained by the polarization correlation imaging method of the present application. This image effectively suppresses the scattered light in the underwater environment by collecting the horizontal polarization light intensity I ∥ and the vertical polarization light intensity I ⊥ , and combines the second-order polarization correlation algorithm, making the boundary and contour of the oil spill area clearer. Specifically: the black and white contrast of the image is relatively significant, forming a distinct contrast between the oil spill area and the background water body, making the edge features of the oil spill prominent. Compared with the traditional underwater polarization imaging method, the polarization correlation imaging method of the present application can more effectively eliminate the influence of scattered light and present a more real and clear oil spill contour.

[0057] Figure 7 Shows the oil spill detection image after integrating the traditional underwater polarization imaging method and the polarization correlation imaging method of the present application. 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: compared with Figure 6In contrast, the fusion method makes the oil spill boundary more natural, with a certain transitional effect. This improvement may benefit from the introduction of traditional imaging techniques, which enables the image to retain more background information while removing scattering. Through fusion processing, the brightness of the image is enhanced, the laser signal intensity after reflection in the oil spill area is significantly increased, and the overall imaging quality is further improved.

[0058] By comparing these two images, the application effects of different imaging techniques in underwater oil spill detection can be clearly seen. The polarization correlation imaging method of this application has outstanding advantages in removing scattered light, and the combination with traditional imaging methods further improves the imaging effect, providing a more accurate solution for underwater oil spill detection.

[0059] Furthermore, Figure 2 Figure 1 is a schematic diagram of a data acquisition device for an underwater oil spill imaging detection method based on a polarization correlation algorithm, where: Laser 1 is used to emit a laser beam with a wavelength of 532 nm as the light source for underwater oil spill detection.

[0060] Collimating and beam expanding mirror 2 is used to collimate the laser beam emitted from the laser, making the laser beam maintain a parallel state to ensure its high precision during underwater transmission.

[0061] Digital Micromirror Devices (DMD) 3 receives the speckle field sent by the data processing unit to perform optical field control on the light beam, ensuring that the laser can accurately scan the oil spill area.

[0062] Polarization Beam Splitter (PBS) 4 is used to divide the laser beam modulated by DMD into two beams with different polarization states to distinguish the polarization information of the oil spill area.

[0063] First bucket detector 5 and second bucket detector 6 respectively receive the two beams with different polarization states split by PBS to obtain the polarization imaging data of the underwater oil spill. The first bucket detector 5 or the second bucket detector 6 converts the received optical signal into an electrical signal for subsequent analysis and processing.

[0064] Data processing unit 7 is connected to the first bucket detector 5, the second bucket detector 6, and the digital micromirror device 3. It is used to randomly generate a reference speckle and send it to the digital micromirror device 3, receive the electrical signal transmitted by the first bucket detector 5 or the second bucket detector 6, and perform correlation imaging calculation using the underwater oil spill imaging detection method based on the polarization correlation algorithm of this application, and finally generate an underwater oil spill imaging image.

[0065] (1) By combining the polarization correlation imaging model with the traditional underwater polarization imaging model, this application breaks through the limitations of traditional technologies in dealing with the influence of scattered light in complex underwater environments. Polarization correlation imaging utilizes the horizontal and vertical polarization information of the reflected laser signal and combines the second-order correlation imaging algorithm to significantly suppress underwater backscattering and improve the contrast and clarity of the image.

[0066] (2) By introducing the polarization degree 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 scenarios, this innovative method not only solves the problem of low processing efficiency of traditional models for backscattered light in complex underwater environments, but also can more precisely correct the polarization information of the reflected laser signal, better recover the reflected laser signal of underwater target objects, and improve the imaging quality.

[0067] (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 adjustable weight coefficients, it can flexibly adapt to different imaging conditions and effectively improve the effect of scattering removal during imaging. This method is particularly suitable for complex underwater environments, especially when the polarization degree of the reflected laser signal of oil spills on the sea surface has a significant impact on the imaging quality, it can significantly improve the contrast of the image. The signal-to-noise ratio of this polarization correlation algorithm is 30% higher than that of traditional polarization imaging.

[0068] In an exemplary embodiment, a computer device is provided, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement an underwater oil spill imaging detection method based on the polarization correlation algorithm.

[0069] In an exemplary embodiment, a computer device is provided. The computer device can be a server or a terminal, and its internal structure diagram can be as Figure 8As shown in the figure. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, 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 the 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 external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements an underwater oil spill imaging detection method based on a polarization correlation algorithm.

[0070] Those skilled in the art can understand that Figure 8 the structure shown in the figure is only a block diagram of some structures 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 those shown in the figure, or combine some components, or have different component arrangements.

[0071] 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 for analysis, stored data, displayed data, etc.) involved in the present 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 need to comply with relevant regulations.

[0072] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing 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 embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0073] The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logics, data processing logics based on quantum computing, etc., without limitation.

[0074] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, 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, it should be considered to be within the scope described in this specification.

[0075] Specific examples are used in this article to elaborate on the principles and implementation manners of the present application. The descriptions of the above embodiments are only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. An underwater oil spill imaging detection method based on a polarization correlation algorithm, characterized in that, The underwater oil spill imaging detection method based on the polarization correlation algorithm includes: Emitting a laser signal to the sea area to be measured, and collecting the horizontal polarization intensity and vertical polarization intensity of the reflected laser signal; the sea area to be measured includes: an oil spill detection area and a background area; Calculating the polarization correlation image of horizontal polarization and the polarization correlation image of vertical polarization respectively based on the horizontal polarization intensity and vertical polarization intensity of the reflected laser signal; Obtaining a polarization image based on the polarization correlation image of horizontal polarization and the polarization correlation image of vertical polarization; Calculating the degree of linear polarization of the oil spill detection area and the degree of linear polarization of the background area based on the polarization image; Obtaining the intensity value of the reflected laser signal in the oil spill detection area based on the polarization correlation image of horizontal polarization, the polarization correlation image of vertical polarization, the degree of linear polarization of the oil spill detection area, and the degree of linear polarization of the background area; Calculating the background scattered light intensity in the reflected laser signal based on the degree of linear polarization of the background area; Calculating the correction factor of the reflected laser signal in the oil spill detection area based on the polarization correlation image of horizontal polarization, the polarization correlation image of vertical polarization, and the background scattered light intensity; Determining the transfer function based on the horizontal polarization intensity, vertical polarization intensity, background scattered light intensity, degree of linear polarization of the background area, and the correction factor; Determining the image after de-scattering restoration based on the transfer function, the background scattered light intensity, and the intensity value of the reflected laser signal in the oil spill detection area, and taking the image after de-scattering restoration as the underwater oil spill imaging image.

2. The underwater oil spill imaging detection method based on the polarization correlation algorithm according to claim 1, wherein The calculation formula for the polarization correlation image of horizontal polarization is: ； Among them, represents the polarization correlation image of horizontal polarization; represents the spatial distribution of the speckle field generated for the k-th time on the DMD; represents the light intensity value in the horizontal polarization direction; represents the ensemble average; The calculation formula for the polarization correlation image of vertical polarization is: ； Among them, represents the polarization correlation image of horizontal polarization; represents the light intensity value in the vertical polarization direction.

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

4. The underwater oil spill imaging detection method based on the polarization correlation algorithm according to claim 3, characterized in that, The calculation formula for determining the polarization image is: ； Among them, represents the polarization image; represents the horizontal polarization degree of the nth pixel point; represents the vertical polarization degree of the nth pixel point.

5. The underwater oil spill imaging detection method based on the polarization correlation algorithm according to claim 4, wherein The calculation formula for the intensity value of the reflected laser signal in the oil spill detection area is: ； Among them, I obj represents the light intensity value of the reflected laser signal in the oil spill detection area; P bg represents the degree of linear polarization of the background area; P ob represents the degree of linear polarization of the oil spill detection area.

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

7. The underwater oil spill imaging detection method based on the polarization correlation algorithm according to claim 6, wherein The calculation formula for the correction factor of the reflected laser signal in the oil spill detection area is: ； Among them, represents the correction factor of the reflected laser signal in the oil spill detection area; represents the medium light intensity of the parallel polarization state at infinity; represents the medium light intensity of the perpendicular polarization state at infinity.

8. The underwater oil spill imaging detection method based on the polarization correlation algorithm according to claim 7, characterized in that Determining the transfer function based on the horizontal polarization intensity, vertical polarization intensity, background scattered light intensity, degree of linear polarization of the background area, and the correction factor, specifically including: Determining the difference value of the light intensity of the polarization orthogonal image based on the horizontal polarization intensity and the vertical polarization intensity; A weight coefficient is introduced, and the transfer function is determined based on the difference value of the light intensities of the polarization-orthogonal images, the light intensity of the background scattered light, the linear polarization degree of the background region, and the correction factor.

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

10. A computer device, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein 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 1-9.

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