62 results about "Underwater imaging" patented technology

The invention discloses an underwater image enhancement method and system based on binocular vision and polarization imaging. The method comprises the following steps: firstly, synchronously acquiring an orthogonal polarization image pair through a binocular polarization imaging unit, recovering scene depth information from the polarization image pair by using a binocular stereoscopic vision technology, and calculating a transmissivity graph; analyzing the polarization characteristic difference between target reflected light and backscattered light, establishing a polarization difference model, and separating background scattered light; solving an underwater imaging equation in combination with the depth information and a polarization difference model to obtain a preliminary restoration result of the target reflected light; and finally, further improving the image quality through the steps of multi-scale spectrum analysis, adaptive filter construction and post-processing by adopting a spectrum adaptive image enhancement technology. The system comprises a binocular polarization imaging unit, a calculation processing unit and an active illumination unit. According to the method, the problems of color distortion, low contrast and fuzzy details of the underwater image are solved, and the visual quality and usability of the underwater image are improved.

The invention provides an underwater target detection system and method for an AUV-carried synthetic aperture sonar, and belongs to the technical field of underwater acoustic detection. The method comprises the following steps: transmitting an ultra-wideband sound wave signal to an underwater target, and collecting an echo signal by using receiving array elements which are non-uniformly and sparsely arranged along a track direction; preprocessing the echoes and decomposing the echoes into a plurality of non-overlapping sub-band signals, obtaining an equivalent space response by calculating inter-channel phase differences under each sub-band, and further constructing a joint observation matrix; and high-resolution azimuth scattering intensity distribution is recovered in combination with compressed sensing, and motion compensation is performed by using platform motion data to realize underwater imaging. According to the invention, the dependence of the traditional synthetic aperture technology on long-distance uniform-speed motion is broken through, and high-resolution and high-precision underwater target detection and imaging can still be realized under the condition of high-speed navigation of an AUV (Autonomous Underwater Vehicle).

The invention discloses a three-dimensional Gaussian splash reconstruction method for an underwater scene, and belongs to the technical field of computer vision and three-dimensional reconstruction. Comprising the following steps: acquiring a monocular video frame sequence of a target underwater scene, a corresponding camera pose sequence, an initial sparse point cloud, an initial three-dimensional Gaussian point set and learnable physical parameters of an underwater imaging model; in the training process, performing weighted evaluation on a reconstruction error based on a multi-view consistency mechanism of opacity weighting, calculating an importance score of each Gaussian point, and performing densification operation on a three-dimensional Gaussian point set; adopting a staged freezing strategy to cooperatively optimize the three-dimensional Gaussian point set and underwater imaging model parameters; and performing rendering and underwater image synthesis on any new view angle camera pose based on the optimized three-dimensional Gaussian point set and underwater imaging model parameters, and outputting a new view angle synthesized image to represent a reconstruction result. According to the method, the geometric compactness, the visual fidelity and the physical interpretability of an underwater three-dimensional reconstruction result are improved.

The invention relates to the technical field of underwater detection, discloses a remote synchronous synthetic aperture sonar cluster acoustic compatibility method, and solves the problem of mutual interference caused when multiple synthetic aperture sonars of the same model carry out detection in the same area. The method comprises the following steps: acquiring the state position and course information of a cluster sonar unit; predicting a future track and a sonar underwater irradiation area based on extended Kalman filtering; an orthogonal frequency modulation emission signal is dynamically generated; on the basis of receiving mixed echoes, carrying out iterative interference cancellation by using known waveform information; and a sparse reconstruction theory is combined to recover a full-bandwidth target echo, and the full-bandwidth target echo is finally used for generating a high-resolution interference-free sonar image. The system comprises a state acquisition module, a track prediction module, a waveform generation module, a transmit-receive control module, an interference cancellation module, a frequency spectrum reconstruction module and an imaging module, and collaborative optimization of sonar interference suppression and underwater high-resolution imaging is realized.

The invention relates to the technical field of underwater imaging, provides a Fourier lamination underwater imaging system and method based on adaptive phase retrieval, and effectively solves the problem of insufficient imaging resolution caused by a strong scattering effect of a water body and aperture limitation of an optical system in a traditional underwater imaging technology. According to the method, the Fourier lamination imaging technology is applied to the underwater environment for the first time, and the spatial resolution is improved by 2.24 times compared with that of a traditional method in combination with the self-adaptive phase retrieval algorithm. Further experiments show that even under the strong scattering condition, the scheme can still keep the resolution performance obviously superior to that of a traditional method. The invention provides a novel underwater high-resolution imaging technical scheme, the imaging performance of marine resource exploration and underwater engineering facility detection can be remarkably improved, and the method has important application value.

The invention relates to the technical field of underwater imaging equipment, and discloses an underwater variable baseline stereoscopic vision imaging system, which comprises a mounting plate, a lifting mechanism is arranged at the lower part of the mounting plate, the lifting mechanism is used for driving a direction adjusting cylinder to lift, a direction adjusting mechanism is arranged in the direction adjusting cylinder, and the direction adjusting mechanism is used for adjusting the direction of the direction adjusting cylinder. The direction adjusting mechanism is used for adjusting the direction of the groove frame, the groove frame is provided with an angle adjusting mechanism, the angle adjusting mechanism is used for adjusting the angle of the shell, continuous adjustment of the baseline length of the left camera and the baseline length of the right camera can be synchronously achieved, and the visual angle included angle between the two cameras is adjusted in a linkage mode. It is ensured that the imaging system always maintains a stable imaging geometrical relationship and reasonable field-of-view overlapping; the design has the advantages of being compact in structure, easy and convenient to control, sensitive in response and the like, is particularly suitable for underwater stereoscopic vision imaging tasks in a dynamic change environment, and has good engineering application prospects.

This invention provides an underwater long-range ultra-high-definition polarization imaging system and method, relating to the field of data processing technology. The system comprises, from bottom to top, an optical sensing layer, a physical computing layer, an AI inference enhancement layer, an adaptive control layer, and a decision optimization layer, forming a hierarchical control structure where data flows upward and strategies are passed downward. The optical sensing layer employs a non-uniform polarization sampling array, a spectral polarization joint coding unit, and a dual-modal illumination unit to simultaneously acquire intensity, multi-directional polarization, multispectral images, and depth information. The physical computing layer calculates polarization parameters in real time and inverts water turbidity within the image signal processor hardware pipeline. The AI ​​inference enhancement layer embeds the physical model as a differentiable module into a neural network to achieve scattering suppression and detail enhancement. The adaptive control layer adopts a time-scale separated dual-closed-loop architecture. This invention can adapt to different water turbidity levels, output ultra-high-definition images in real time, and significantly improve the quality of long-range underwater imaging.

The invention discloses an underwater binocular camera calibration method based on laser assistance, and the method comprises the steps: firstly constructing an underwater stereoscopic vision binocular refraction-removing imaging model according to the Snell's law, and correcting an underwater imaging error; secondly, acquiring a camera internal reference matrix by using a Zhang Zhengyou calibration method; then, a laser range finder is used for projecting laser to the calibration plate to form a light spot, the center pixel coordinate of the light spot is extracted through a gray gravity center method, the three-dimensional coordinate of the light spot is calculated in combination with laser ranging data, and the initial value of an external parameter matrix of the binocular camera is solved; and finally, introducing a Bayesian optimization algorithm, and optimizing the constraint equation by taking minimization of a three-dimensional coordinate calculation error as a target so as to obtain an exact solution of an external parameter matrix of the camera. Through organic combination of a deep learning technology and binocular stereo vision, the parameter calibration precision of the underwater binocular stereo vision camera is improved, a reliable technical guarantee is provided for subsequent underwater concrete structure defect quantification, and the fine monitoring requirement in a complex water environment is met.

This invention discloses an underwater image enhancement method and system based on physical priors and target features, belonging to the field of image processing technology. To address the technical problem that existing underwater image enhancement methods struggle to simultaneously achieve imaging physical consistency, visual quality, and usability for downstream target recognition tasks, this invention extracts physical prior information from underwater images, including transmittance maps and background illumination maps; acquires target features from underwater images; extracts image features from underwater images through an enhancement network; and fuses and reconstructs image features, physical prior information, and target features to obtain an enhanced image; trains the enhancement network; and uses the trained enhancement network to process underwater images to obtain the enhanced image. This invention achieves high-quality visual restoration while satisfying the physical constraints of underwater imaging, and significantly improves the accuracy of underwater target recognition and the performance of related downstream tasks.

The invention belongs to the technical field of underwater image enhancement perception, and particularly relates to a double-branch cross decoupling deepwater image enhancement method and system and a storage medium. The method comprises the following steps: acquiring an original underwater image, and inputting the original underwater image into a multi-stage encoder; extracting a general feature map in a multistage encoder, setting a detail reconstruction branch and a color correction branch, performing branch-oriented feature enhancement, performing gating modulation cross fusion on the enhanced features, and outputting a feature map; inputting the feature map into a multi-stage decoder and a prediction head to obtain a transmissivity map and a three-dimensional vector of global background light; and substituting the transmissivity graph and the three-dimensional vector of the global background light into an underwater imaging model formula for inverse processing to obtain a clear deepwater image. The problems that the image is easy to degrade in a deepwater non-uniform illumination environment, and an existing underwater image enhancement method depends on big data, is complex in training or consumes time in post-processing, and is difficult to adapt to ARV lightweight deployment requirements are solved.

An underwater image restoration method based on polarization degree image clustering belongs to the field of image processing, and comprises the following steps: constructing a physical model of underwater imaging; a polarization image is collected, a Stokes vector is calculated, and meanwhile the polarization degree and the polarization angle of the scene are calculated according to the Stokes vector; calculating a brightest polarization image and a darkest polarization image; performing coarse clustering and fine clustering on the polarization degree image, and separating a background region from a target region; and local adaptive optimization is carried out based on an adaptive optimization method of an evaluation index, and image restoration is carried out by using a gain item. The background area can be automatically selected without manual intervention; the back scattering value of each small block can be estimated and optimized in a robust mode through iteration based on evaluation given by the evaluation indexes, the target polarization degree and the background polarization degree of the image are adjusted according to block characteristics, and the recovery effect of the whole image is improved. According to the method, a clear underwater image can be recovered, the visibility and the contrast ratio of the image are improved, and color distortion is corrected at the same time.

The invention relates to an underwater low-light image recovery method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining and processing an original underwater polarization image, and calculating an orthogonal polarization image; three parallel depth image prior networks are constructed and initialized, and are respectively used for generating direct transmission light and orthogonal polarization backscattered light; the network is jointly optimized under polarization physical constraints, and accurate decoupling and illumination recovery of scattering components are realized by minimizing a total loss function formed by reconstruction loss, polarization differential loss, polarization degree reconstruction loss and adaptive stretching loss; and recovering a final underwater clear image according to an underwater imaging model by using direct transmission light and backscattering light generated by the optimized network. According to the method, advantages of a physical imaging model and data driving are effectively fused, and robust and high-quality underwater image restoration is realized specially for complex degradation of an underwater low-light scene.

The invention discloses a decoupling cooperative enhancement method for an underwater image degradation factor, and belongs to the technical field of underwater image enhancement. Aiming at the problem that an underwater imaging environment is complex and changeable, and light propagation is influenced by wavelength selective absorption and suspended particle scattering to cause image degradation, a degradation factor is approximately decomposed into relatively independent scattering degradation and color cast degradation, and a binarization strategy is introduced to compress the storage and calculation amount of data, so that the image degradation is realized. And global information is compensated in back propagation through decoupling learning, and data compression precision loss is recovered. According to the decoupling collaborative optimization method, scattering and color problems are distributed to a physical compensation module and a spectrum compensation module, learning information is isolated through a gating mechanism, and degeneration decoupling is achieved; the loss function is combined with the subtasks and the global loss to compensate the binarization precision loss of the submodules, and finally, the modules are cascaded to process and recover the degraded image.

The invention belongs to the technical field of intelligent fishery and underwater imaging, and discloses a distance-adjustable matte background plate and body width estimation camera device for an intelligent fishing system, which comprises a distance-adjustable matte background plate arranged in a recognition box and a body width estimation camera mounted near a sensor. The background plate is driven by a waterproof electric driver to realize dynamic adjustment of the imaging distance; and the control processor automatically adjusts the position of the background plate based on the fish body width and the water body turbidity parameter so as to obtain the optimal imaging effect. Scale marks are arranged on the surface of the background plate and used for measuring the length of a fish body. The background plate can be in a linear type or a front-arc and rear-straight combined type, and has the function of expelling fish bodies when being slowly propelled. The method can significantly improve the fish identification success rate under the natural water body condition, and is suitable for scientific research, resource protection and smart fishery application.

The invention discloses an underwater range gating dynamic imaging method based on meta-heuristic attitude estimation, and relates to the technical field of underwater imaging, and the method comprises the steps: building an underwater range gating laser imaging system, and obtaining a continuous space-time matched original scanning image sequence through synchronous control of laser emission, scanning and gating exposure; selecting a reference frame from an original scanning image sequence, determining an effective imaging area, modeling inter-frame rigid body motion by adopting a six-degree-of-freedom pose parameter, and constructing a global optimization objective function based on a gray mean square error; and designing a self-adaptive weighted pixel loss function, distributing weights for pixels through normalized gray and gradient information, and inhibiting the influence of a highlight area. According to the method, the meta-heuristic optimization thought is applied to the 6D pose estimation problem of underwater range gating laser imaging, a 6D pose optimization framework suitable for a high-sparseness and high-constraint scene is constructed based on PSO, and the fundamental challenges of scarcity of feature points and insufficient data sets are overcome.

The invention discloses an underwater scene semantic segmentation method based on SAM2 physics driven fusion and adaptive prompt, and relates to the field of deep learning. Selecting underwater scene images and depth maps and real semantic segmentation images corresponding to the underwater scene images, and forming a training set; introducing the classical underwater imaging physics model into RGB-D semantic segmentation, and constructing a convolutional neural network; pre-processing a training set, and inputting the pre-processed training set into the convolutional neural network for training to obtain a corresponding predicted underwater scene semantic segmentation image; calculating and predicting a loss function value between the underwater scene semantic segmentation image and the corresponding real semantic segmentation image, and training for multiple times until the loss function value accords with a preset threshold value to obtain an underwater scene semantic segmentation network model; and inputting an image to be segmented into the underwater scene semantic segmentation network model to obtain a segmentation result. According to the method, high-precision segmentation of a complex underwater scene is realized, and the automation degree and robustness of segmentation are improved.

This invention discloses an underwater range-gated dynamic imaging method based on metaheuristic attitude estimation, belonging to the field of underwater imaging technology. The method includes: constructing an underwater range-gated laser imaging system; acquiring a continuous, spatiotemporally matched sequence of original scanned images by synchronously controlling laser emission, scanning, and gated exposure; selecting reference frames from the original scanned image sequence and determining the effective imaging region; modeling inter-frame rigid body motion using six-degree-of-freedom pose parameters; constructing a global optimization objective function based on gray-level mean square error; and designing an adaptive weighted pixel loss function, assigning weights to pixels by normalizing gray-level and gradient information to suppress the influence of bright areas. This invention applies metaheuristic optimization ideas to the 6D pose estimation problem of underwater range-gated laser imaging, constructing a 6D pose optimization framework suitable for highly sparse and highly constrained scenarios based on PSO, overcoming the fundamental challenges of feature point scarcity and insufficient datasets.

This invention provides an acoustic imaging method based on the enhancement of three-dimensional features of underwater targets, comprising: establishing an underwater three-dimensional acoustic imaging model; dividing the imaging area into multiple two-dimensional spherical slices centered at the sound source; discretizing each spherical slice into a set of grid points; constructing a signal receiving model; constructing a three-dimensional L1-TV norm optimization problem based on the underwater three-dimensional acoustic imaging model to enhance the three-dimensional features of the underwater target; decomposing the three-dimensional L1-TV norm optimization problem into several sub-problems using the alternating multiplier method; solving each sub-problem based on the Chambolle projection method and the near-end mapping algorithm to obtain its analytical or numerical solution, thereby achieving three-dimensional imaging of the underwater target. This invention effectively utilizes the three-dimensional features of the underwater imaging area and the contour information of the underwater target, resulting in fewer artifacts in the imaging results, clearer target contours, and improved imaging quality.

The invention relates to a robot device for underwater concrete crack detection. The robot device comprises an external supporting frame, an equipment cabin, a camera, a cleaning rotary brush and a propelling system. The composite optical observation window has the beneficial effects that the composite optical observation window is a three-layer optical cabin, a clear water layer is filled with water, and a water body is directly taken from a clear part of an operation water area, so that the optical consistency of the clear water layer and an external water area is ensured, the three-layer optical cabin fundamentally solves the problems of optical distortion and blurring of underwater imaging, and a clear image is obtained; the integrated rotating brush can clear surface attachments before imaging, meanwhile, the pair of cleaning rotating brushes are symmetrically installed on the two sides of the composite optical observation window, and the telescopic position is accurately controlled through a servo motor. The synchronous control technology is adopted for the rotating brush driving motors, it is guaranteed that the two cleaning rotating brushes rotate oppositely in the reverse direction at the constant speed all the time, the cleaning rotating brushes can be accurately controlled to stretch out or retract in the direction parallel to the central axis of the shell, torque is eliminated through the contra-rotating design, and the cleaning process is stable.

The application discloses a kind of underwater imaging quality evaluation methods based on UTOD, belong to underwater detection and imaging technical field, this method includes obtaining triangle target feature, and the image obtained is processed by human eye visual system HVS simulation module;Underwater triangle direction discrimination threshold UTOD model is constructed, and UTOD model is used to distinguish the direction of triangle target;Contrast-sharpness comprehensive index UICS is constructed, including underwater sharpness index and underwater contrast index;Based on four options forced choice 4AFC test, the direction discrimination correct probability corresponding to different UICS values is counted, and the relationship curve of UICS and correct probability is fitted by psychometric function Weibull;Triangle target of different size is repeatedly tested, and UTOD curve is generated.The application realizes automatic target detection and direction identification, and improves the accuracy, stability and objectivity of evaluation index.

The application discloses an underwater image enhancement method, device, equipment and medium, and the method comprises the following steps: acquiring an original underwater image, performing contrast stretching on the original underwater image to obtain a first image; performing image decomposition on the first image to obtain a base layer and a detail layer of each channel; performing red channel compensation on the base layer of the red channel according to the detail layer of the green channel or the detail layer of the blue channel to obtain a compensated red channel; merging the compensated red channel, the green channel and the blue channel to obtain a second image; and performing color correction on the second image to obtain a target underwater image. According to the application, the contrast of the underwater image is stretched, and the image is decomposed and the red channel is compensated to realize color difference attenuation compensation, so that the quality of the underwater image is improved. The application can process the underwater image without relying on an underwater imaging system, so that the quality of the underwater image is improved, and the application can be widely applied in the technical field of image processing.

The application discloses a multi-receiving array synthetic aperture sonar imaging method and device considering intrapulse motion, and comprises the following steps: under the condition that the relative motion speed of a platform in a signal transmitting and receiving pulse width is unchanged in a pulse repetition period, an echo baseband signal model in a two-dimensional plane is established; envelope time delay and phase of an echo baseband signal in the echo baseband signal model are error analyzed based on a waveform scaling factor, and an approximate signal model of the echo baseband signal model is determined; two-dimensional frequency spectrum of an approximate echo baseband signal in the approximate signal model is solved; and focusing is completed by using a single station imaging algorithm based on the two-dimensional frequency spectrum, so that a multi-receiving array synthetic aperture sonar imaging result is obtained. The application realizes multi-receiving array synthetic aperture sonar imaging under the condition of considering intrapulse motion, and improves the resolution of underwater imaging.

This invention discloses an underwater high-repetition-rate pulsed laser line scanning imaging system and method, relating to the field of underwater laser imaging technology. The system includes a laser emission module for emitting high-repetition-rate pulsed lasers, comprising a 532nm high-repetition-rate pulsed laser and a beam shaping module; the beam shaping module consists of a biaxial conical mirror and a cylindrical mirror. A laser imaging module is used for large-depth-of-field imaging of target reflected echoes within a set time window, including a high-speed gated camera, an imaging lens, and a narrowband filter, constructed based on the Sham imaging principle. A synchronization control module is used for power supply, communication, and gating timing control to achieve timing synchronization between the laser and the camera in the system. This invention combines laser line scanning with range-gated imaging technology, making it suitable for long-range, large-area environmental detection as well as high-precision 3D reconstruction of close-range targets, effectively improving the clarity, signal-to-noise ratio, and applicability of underwater imaging.

The invention discloses an underwater image enhancement method and system based on physical prior and target features, and belongs to the technical field of image processing. In order to solve the technical problem that an existing underwater image enhancement method is difficult to consider imaging physical consistency, visual quality and downstream target identification task availability at the same time, physical prior information is extracted based on an underwater image, and the physical prior information comprises a transmissivity image and a background light image; obtaining target features based on the underwater image; extracting image features of the underwater image through an enhancement network, and fusing and reconstructing the image features, the physical prior information and the target features to obtain an enhanced image; and training the enhancement network, and processing the underwater image by using the trained enhancement network to obtain an enhanced image. According to the method, the purposes of realizing high-quality visual restoration on the premise of meeting underwater imaging physical constraints and remarkably improving underwater target recognition precision and related downstream task performance can be achieved.

The application provides a high-integration embedded underwater multi-modal real-time polarization imaging detection system and belongs to the technical field of underwater optical imaging. The application aims at solving the problems of poor imaging effect and insufficient real-time processing capacity of the existing underwater imaging technology in turbid water quality environment. The system comprises an LED light source, a collimated light beam module, a polarized light source module, an image acquisition and processing module and a waterproof pressure-resistant sealed cabin.

The application discloses a solar-ocean energy complementary power supply system for underwater imaging and relates to the technical field of ocean engineering equipment and new energy utilization. The system comprises a water floating buoy unit and an underwater imaging unit. The water floating buoy unit is provided with a solar power generation module, a wind power generation module, an energy storage battery module and an energy management module. The underwater imaging unit is provided with an underwater wave power generation module and an underwater imaging instrument. The application realizes long-term, stable and unattended operation of the underwater imaging equipment by means of multi-energy complementary power supply of solar energy, wind energy and wave energy and intelligent energy management, and solves the problems of poor stability and insufficient endurance of single power supply mode.

The invention discloses an underwater imaging method and system based on light spot distance measurement and a neural network, and belongs to the technical field of underwater imaging, and the method comprises the steps: S100, carrying an adjustable polaroid through underwater camera equipment, adjusting the angle of the polaroid, and collecting a multi-angle polarization image sequence of a target scene; s200, controlling the blue-green wave band laser to project a nonlinear light spot pattern to the target for distance measurement; s300, constructing a refraction correction model according to the refraction offset vector, and restoring the real form of the light spot; s400, fusing the spatial information of the multi-angle polarization image and the target distance data to generate a depth map; s500, registering the polarization texture features and the light spot geometric features based on a graph optimization algorithm, and minimizing a re-projection error; s600, inputting the registered features and the improved depth map into a pre-trained depth enhanced neural network; and S700, further post-processing optimization is carried out on the depth map output by the deep neural network based on a Transform network fusion algorithm. According to the invention, a finer absolute depth map can be provided.

The invention relates to the technical field of coal mine detection, and discloses a mining high-turbidity water body image taking device which comprises a first shell, an industrial camera is rotatably connected to the interior of the first shell, an auxiliary shell is fixedly connected to the side, close to the industrial camera, of the interior of the first shell, and annular teeth are fixedly connected to the surface, close to the detection end, of the industrial camera. A baffle is fixedly connected to the side, close to the annular teeth, of the interior of the first shell, a t-shaped block and a driving assembly are fixedly connected to the interior of the baffle, and the driving assembly comprises a motor fixedly connected to the interior of the auxiliary shell. According to the cleaning device, an imaging area affected by pollution can be rapidly replaced, the cleaning device can be matched with rotary motion of an industrial camera, a used replacement film is rapidly rolled to the position of a replacement rod, efficient and continuous cleaning operation is achieved, installation is convenient and fast, and the definition of underwater imaging and the reliability of monitoring work are remarkably improved.

This invention discloses a vision-based method and apparatus for locating the wellhead of a deepwater blowout preventer (BOP). The deepwater BOP is equipped with at least two sets of deepwater cameras. The method includes: simultaneously acquiring multiple images of the underwater wellhead using the at least two sets of deepwater cameras; symmetrically placing multiple position markers on the upper surface of the wellhead; extracting multiple coordinates corresponding to the position markers in an image acquired by any deepwater camera, and obtaining the wellhead center image coordinates based on these coordinates; calculating the three-dimensional coordinates of the wellhead center in the positioning measurement coordinate system based on the underwater imaging model of the cameras, combined with the intrinsic and extrinsic parameters, underwater refraction parameters of the at least two sets of deepwater cameras, and the wellhead center image coordinates of each image acquired by the at least two sets of deepwater cameras; and determining the relative position information between the wellhead and the deepwater BOP based on the three-dimensional coordinates of the wellhead center. High-precision positioning of the relative position is achieved based on non-contact monitoring.

The application discloses a wide-view field elongated underwater imaging system for fishing in a large-depth well, which comprises a flat pressure window, a first lens, a second lens, a third lens, a fourth lens, a first cemented lens, a second cemented lens, a fifth lens, a third cemented lens, a sixth lens, a filter and a seventh lens which are sequentially arranged from an object plane to an image plane along a light path. The wide-view field elongated underwater imaging system for fishing in a large-depth well has the characteristics of a long optical total length while ensuring a small optical aperture, so that the system can well adapt to a narrow and long environment in an oil well casing, form a good heat buffer, avoid camera failure caused by a high-temperature environment in the well, and has a large underwater view field and a large depth of field, effectively increases the imaging range of the system, and improves the efficiency of fishing operation in the well. The flat pressure window made of sapphire can bear a water depth pressure of more than 3000 meters.