2431 results about "Image plane" patented technology

The invention discloses a coal bunker reserve real-time monitoring method integrating a laser radar and a camera. The method comprises the following steps: step 1, carrying out space-time joint calibration and hardware-level synchronization on a laser radar and a camera, and establishing a projection relationship between a point cloud and an image; 2, cooperatively collecting coal bunker data based on the calibration parameters, and obtaining a point cloud and a high-resolution image; step 3, heterogeneous preprocessing is carried out on the collected point cloud and the image, denoising, segmentation and down-sampling are carried out on the point cloud, semantic segmentation is carried out on the image, and coal and foreign matters are identified; step 4, based on image texture and point cloud coordinate coupling mapping, reconstructing a three-dimensional model with a semantic tag, projecting the point cloud to an image plane to perform feature matching so as to endow the texture, and fusing image semantic information to correct the model; and 5, dynamically calculating the volume of the coal pile by using the semantic three-dimensional model to realize real-time monitoring of reserves. The system overcomes the limitation of a single sensor, achieves the real-time and high-precision monitoring of the reserves of the coal bunker, and effectively improves the intelligent level of coal bunker management.

The invention provides an optical lens, which comprises seven lenses in total, and sequentially comprises a first lens with negative focal power, a second lens with negative focal power, a third lens with negative focal power, a fourth lens with positive focal power and a fifth lens with negative focal power from an object side to an imaging surface along an optical axis, the object side surface of the second lens is a convex surface, and the image side surface of the second lens is a concave surface; the object side surface of the third lens is a convex surface, and the image side surface of the third lens is a concave surface; the image side surface of the fourth lens is a convex surface; the fifth lens has positive focal power, and the image side surface of the fifth lens is a convex surface; the object side surface of the sixth lens is a concave surface, and the image side surface of the sixth lens near the optical axis is a convex surface; and the object side surface of the seventh lens is a concave surface near the optical axis, and the image side surface of the seventh lens is a convex surface. According to the optical lens provided by the invention, through specific surface shape matching and reasonable focal power distribution, the imaging quality of the optical lens is improved, and the lens has one or more advantages of ultra wide angle, ultra large aperture, large image plane, high pixel, high imaging quality and the like.

The invention belongs to the technical field of position tracking control of rigid multi-joint mechanical arms, and discloses a fuzzy self-adaptive visual servo control method and system for a multi-joint mechanical arm system for placing bobbins in a textile workshop, and the method comprises the steps: constructing an image error model according to the positions of feature points on an image plane; the fuzzy logic system is used for processing uncertain items in the system, the instruction filtering and fuzzy self-adaption technology is used for achieving tracking control over the expected trajectory of the system, the problem of calculation complexity is solved, and adverse effects caused by filtering errors are eliminated. In the process of changing the bobbins, the bobbins are placed on a creel through a multi-degree-of-freedom robotic arm, a clamping jaw at the tail end of the robotic arm is required to accurately grab the bobbins for feeding and discharging, and the requirement for accurate and rapid control of the robotic arm is met, so that research on visual servo control of the robotic arm is of great significance. The method has a good control effect, the problem of calculation complexity in the design process of the controller is solved, the trajectory tracking error is smaller, and the system robustness is higher.

The invention discloses a railway tunnel foreign matter detection method based on radar point cloud and RGB image fusion. The method comprises the following steps: acquiring a laser radar point cloud and an RGB image in a railway tunnel; obtaining an RGB image by using an adversarial network model GAN to judge the abnormal occurrence state of the foreign matter in the railway tunnel, and if the abnormal state of the foreign matter occurs, projecting the obtained laser radar point cloud to an image plane to obtain a dense depth map; processing through a sliding window to obtain data slices which are approximately square; and carrying out data feature extraction, fusion and foreign object target detection on the data slices of the RGB image and the dense depth map by using a fusion target detection network based on the OfficientNet-FPN, and outputting a foreign object target information detection result containing a target category, a position, a confidence coefficient and a distance. According to the railway tunnel foreign matter detection method based on radar point cloud and RGB image fusion, high precision, high efficiency and high reliability of railway tunnel foreign matter detection are realized.

The embodiment of the invention provides an optical detection device which comprises an imaging assembly and a photoelectric detection device, and the imaging assembly is used for forming an image on an image plane of a to-be-detected area of a wafer. And the photoelectric detection device is used for receiving images and is arranged at the image plane. The photoelectric detection device comprises a light beam separation assembly and a sensor assembly, the light beam separation assembly is used for dividing a continuous first light signal in an image into multiple beams of second light signals, and the light beam separation assembly comprises a microlens array. The sensor assembly is used for receiving multiple beams of second optical signals, and each pixel unit of each sensor in the sensor assembly is used for receiving one beam of second optical signal in the multiple beams of second optical signals. The sensor assembly comprises a single-pixel sensor, and the single-pixel sensor corresponds to one micro lens in the micro lens array; and / or, the sensor assembly comprises a multi-pixel sensor, the multi-pixel sensor corresponds to a plurality of microlenses in the microlens array, and spatial segmentation is beneficial to improving the signal-to-noise ratio.

The invention provides an optical lens, which comprises eight lenses with focal power and sequentially comprises a first lens with negative focal power, a second lens with positive focal power, a third lens with negative focal power, a fourth lens with negative focal power, a fifth lens with negative focal power and a sixth lens with negative focal power from an object side to an imaging surface along an optical axis, the object side surface of the second lens is a convex surface, and the image side surface of the second lens is a concave surface; the third lens has negative focal power, the object side surface of the third lens near the optical axis is a convex surface, and the image side surface of the third lens is a concave surface; the fourth lens has positive focal power; the object side surface of the fifth lens is a convex surface, and the image side surface of the fifth lens is a convex surface; the sixth lens has positive focal power; the seventh lens has negative focal power; and the object side surface of the eighth lens is a convex surface, and the image side surface of the eighth lens is a convex surface. The optical lens provided by the invention has one or more advantages of short focus, large field angle, high imaging quality and the like.

A display device includes a first liquid crystal (LC) layer and a second LC layer arranged between a backlight unit and a linear polarizer, and a multiscopic optical element arranged between the first LC layer and the second LC layer. Drive signals for LC cells of the first LC layer and the second LC layer are generated, based on corresponding images to be presented to each eye of each individual user, a relative location of each eye with respect to an image plane of the display device, and relative positions of the LC cells of the first LC layer and the second LC layer with respect to multiscopic cells of the multiscopic optical element. The LC cells are controlled using the drive signals, to adjust a polarization of light passing therethrough, for producing a synthetic light field presenting the corresponding images to each eye of each individual user.

The invention provides an objective lens module and a photoetching imaging system, and relates to the technical field of optical imaging, the objective lens module is configured between an object plane and an image plane of the photoetching imaging system, and the objective lens module comprises a first lens group, a second lens group and a microobjective lens group which are sequentially arranged from the object plane to the image plane, the first lens group and the second lens group are both of a double-Gaussian structure or a double-Gaussian derivative structure, and the focal length of the first lens group is larger than that of the second lens group. The objective lens module can reduce the aperture size of the optical lens in the objective lens module, increase the object space working distance and improve the imaging quality on the premise of ensuring a large field of view.

The invention relates to a semantic simultaneous localization and mapping method and system based on Gaussian splashing. The method comprises the following steps: firstly, collecting a frame of RGB-D image, modeling a scene into a 3D semantic Gaussian field containing a plurality of 3D semantic gausses according to the RGB-D image, and rendering the 3D semantic gausses by using a tile rasterization technology to obtain 2D image plane gausses; rendering results of RGB color, depth and semantic features are extracted from the 2D image plane in a Gaussian mode, and the semantic features are decoded into semantic tags; constructing a mapping and tracking loss function by using an RGB color rendering result, a depth rendering result, a semantic tag and a truth value, and jointly optimizing a camera pose and a semantic Gaussian field based on a tracking stage and a mapping stage; and repeating the steps for each new frame of RGB-D image to complete the construction of the incremental semantic Gaussian map. Compared with the prior art, the method has the advantages of realizing robust camera tracking, real-time high-quality rendering, accurate 3D semantic reconstruction and the like.

The invention discloses a crack image processing method based on a neural network and plane geometry image transformation, and particularly relates to the field of general image data processing driven by plane geometry image transformation and neural network identification. Comprising the steps that an image collection platform projects a structured image coding pattern to the surface of a to-be-measured target through a preset image coding pattern template, and synchronously collects an image frame containing an image mark so as to construct a space anchor point used for image geometric reference in an image plane; view angle parameter change information in an image acquisition process is acquired through an image acquisition platform, and projection configuration parameters of an image coding pattern are combined. By constructing an image offset modeling mechanism jointly driven by an image coding pattern and a space anchor point, image in-plane correction of geometric distortion features in an image frame is realized, and structural consistency and texture continuity before subsequent image analysis are improved.

The invention provides a high-dynamic deformation measurement system and method based on laser section contour differential scanning. The measurement system is composed of a section contour measurement unit, a calibration unit, an error compensation unit and a data processing unit, wherein the section contour measurement unit comprises a multi-sight-line structured light sensor module, a speed sensing module and a distance measurement module; the calibration unit comprises a synchronous control module, an adjustment module and a common tooth-shaped calibration target; the error compensation unit comprises a vibration detection module, a posture detection module and a temperature detection module; the data processing unit is a device with programming and computing functions. The measuring method comprises the following steps: (1) calibrating a laser plane and an image plane; (2) unifying a global coordinate system; (3) obtaining point cloud data; (4) error compensation; (5) constructing a deformation time-history model; and (6) carrying out maximum deformation global optimization. According to the measurement system and method, accurate expression and maximum value global optimization of a pavement micro-deformation three-dimensional space under the load effect can be realized.

The invention provides a metasurface structure design method and a metasurface structure, and the method can comprise the steps: initializing a rotation angle of the metasurface structure; a first light field construction step: constructing a transmission light relation of the current metasurface structure based on the rotation angle; a second light field construction step: constructing a diffracted light relationship of the current metasurface structure based on the transmitted light relationship so as to determine the light intensity distribution of the image plane; an error construction step: calculating an iteration constraint value according to the image plane light intensity distribution and the target light intensity; wherein the target light intensity is a preposed parameter, the target light intensity is the light intensity corresponding to the target metasurface structure, and the target metasurface structure is a design target; if it is judged that the iteration constraint value is larger than the set value, the rotation angle is updated, the updated rotation angle is obtained, the first light field construction step, the second light field construction step and the error construction step are repeatedly executed till the iteration constraint value is not larger than the set value, and the target metasurface structure is determined based on the current rotation angle.

The invention discloses a digital human rendering method based on Gaussian splashing and multi-scale characteristic field distillation, and belongs to the field of three-dimensional human body digital reconstruction. According to the method, feature extraction is carried out through a Vision Transformer encoder, based on an SMPL model, through a cross-modal parameter estimation module and dynamic human body modeling of three-dimensional Gaussian splashing and semantic feature rendering, three-dimensional Gaussian is projected to a two-dimensional image plane to calculate a covariance matrix and color mixing, and after a rendered color image and an initial feature field image are output, a three-dimensional image is obtained. A student feature map is obtained through a convolution acceleration module, a teacher feature map is obtained after feature extraction is carried out through a two-dimensional basic model, the constructed model is trained, and optimization training is completed through comprehensive total loss function calculation; according to the method, the problems of fuzzy semantics, detail missing, low rendering efficiency and inaccurate human body-scene separation in the existing method are effectively solved, so that more efficient, fine and robust monocular or multi-view human body three-dimensional reconstruction is realized.

The invention discloses a teleconverter lens. The teleconverter lens comprises a system front group and a system rear group, the system front group comprises a first lens group and a second lens group, and the system rear group comprises a third lens group and a fourth lens group; the first lens group comprises a first lens, a second lens, a third lens, a fourth lens and a fifth lens which are sequentially arranged from the object plane to the image plane along the optical axis; the second lens group comprises a sixth lens, a seventh lens, an eighth lens and a ninth lens which are sequentially arranged from the object plane to the image plane along the optical axis; the third lens group comprises a tenth lens and an eleventh lens which are sequentially arranged from the object plane to the image plane along the optical axis; the fourth lens group comprises a twelfth lens and a thirteenth lens; the focal length fz1 of the first lens group and the focal length fz2 of the second lens group satisfy 0.8200 lt; fz1 / fz2lt; the focal length fz3 of the third lens group and the focal length fz4 of the fourth lens group satisfy 1.6800 lt; fz3 / fz4lt; and 7.3000). Therefore, the lengths of front and back groups of the system can be reduced, the total length of the system is less than 120mm, and the characteristic of short total length of the system is achieved.

The invention provides a three-dimensional target marking method and device based on a point cloud data-assisted two-dimensional image, and the method comprises the steps: fusing precise three-dimensional point cloud information obtained by a laser radar and two-dimensional image data collected by a camera based on a point cloud data and image data cooperation three-dimensional marking method; and a dynamic high-precision three-dimensional target marking system is constructed. Specifically, a space-image relationship is established through three-dimensional point cloud information and a two-dimensional image plane, and three-dimensional information of a target is mapped into a two-dimensional image, so that geometric and semantic information labeling is carried out on the target in the two-dimensional image, information loss of two-dimensional visual data in dimensions such as depth, attitude and space structure is made up, and the accuracy of the three-dimensional information labeling is improved. And meanwhile, when the three-dimensional point cloud is unmeasurable, a three-dimensional target labeling mode is dynamically adjusted in combination with two-dimensional image labeling information. According to the method, through dynamic high-precision three-dimensional target labeling, the obtained image-label can be used for training and reasoning of a three-dimensional target detection network, and the method has a wide application prospect.

The invention provides a coal face mining auxiliary method based on visual and point cloud data fusion modeling, and the method comprises the steps: collecting the visual image data of a coal face, collecting the three-dimensional point cloud data through a point cloud sensor, and obtaining the motion state information through an inertial sensor; based on internal and external parameters and IMU data of joint calibration, mapping point cloud data to an image plane, establishing a geometric mapping relationship between three-dimensional points and pixels, generating an attribute point cloud model containing geometry, color and semantics, and generating a high-precision global three-dimensional digital twinning model; and identifying and tracking equipment instances in the digital twinborn model, and resolving motion parameters of key components based on a URDF kinematics model and a principal component analysis algorithm to support remote control decisions. According to the invention, high-precision real-time sensing and three-dimensional visualization of the working space size, the equipment connection relation and the movement position of the coal face can be realized, and the remote control precision and the response efficiency of unmanned mining are remarkably improved.

The invention discloses a multi-sensor fusion-based obstacle detection and recognition method for a wharf unmanned vehicle, and relates to the technical field of intelligent driving, and the method comprises the steps: setting a maximum threshold value and a minimum threshold value, comparing a sensor coverage rate with the maximum threshold value and the minimum threshold value, executing a sensor increase and decrease strategy, and carrying out the time synchronization of sensor data; obtaining an internal parameter matrix, a distortion coefficient and an external parameter matrix, projecting three-dimensional point coordinates of the point cloud data into two-dimensional coordinates of an image plane, and converting the two-dimensional coordinates in the image data into three-dimensional coordinates in a global coordinate system; labeling the sensor data to obtain a two-dimensional bounding box and a three-dimensional bounding box, and obtaining the category and pose label of an obstacle; building a multi-modal fusion perception model, and training the multi-modal fusion perception model by taking the sensor data and the categories and pose labels of the obstacles as training data; and deploying the optimized multi-modal fusion perception model, and outputting the category and pose information of the obstacle, so that the method is suitable for a complex driving environment.

A method and an apparatus for constructing hierarchical semantic map based on deep-learning based perception, a server, a storage medium are provided. The method includes: obtaining 3D point cloud data, scene images and motion state data; projecting 3D point cloud data onto an image plane to obtain a depth image; performing a point cloud registration and a pose prediction on the 3D point cloud data and the motion state data to obtain an odometer pose; generating a point cloud map according to the 3D point cloud data and the odometer pose of multi-sensor system; based on the depth image and the odometer pose of the multi-sensor system, performing an external ellipse fitting process on each semantic region in the depth image to obtain an object-enveloped map for respective object images; fusing the coordinately aligned point cloud map and object-enveloped map into a semantic map.

The utility model discloses a prime lens comprising a front lens group, a diaphragm and a rear lens group which are arranged from an object plane to an image plane along an optical axis. The front lens group comprises a first lens, a second lens and a third lens which are sequentially arranged from the object plane to the image plane, the focal power of the first lens is negative, the focal power of the second lens is negative, and the focal power of the third lens is positive; the focal power of the rear lens group is positive, and the rear lens group comprises a fourth lens, a fifth lens, a sixth lens, a seventh lens and an eighth lens which are sequentially arranged from the object plane to the image plane, the focal power of the fourth lens is positive, the focal power of the fifth lens is negative, the focal power of the sixth lens is positive, the focal power of the seventh lens is negative, and the focal power of the eighth lens is positive; the focal power of the front lens group is phi front, the focal power of the rear lens group is phi rear, and the focal power of the prime lens is phi; wherein-0.085 < = phi front / phi < = 0.25, and 0.35 < = phi rear / phi < = 0.48. Through the lens group and the focal power distribution of each lens, the design of a large-aperture and large-target-surface prime lens can be realized.

The invention discloses a material movement behavior monitoring method and system based on monocular vision, and relates to the field of material movement monitoring, and the method comprises the steps: firstly collecting a material movement video through a monocular high-speed camera, and extracting a continuous state sequence of a material on a two-dimensional image plane through employing an instance segmentation and time sequence tracking technology; the method is characterized in that a time sequence deep learning model is introduced to analyze a state sequence, and a key event that a material collides with a working surface of equipment is automatically identified, so that the collision moment and contact point coordinates are accurately obtained. In this way, the collision contact point is used as a geometric anchor point for three-dimensional space back calculation, a two-dimensional image track is reversely projected and reconstructed into a three-dimensional space motion track in combination with internal parameters of a camera and physical parameters of an equipment reference plane, then key kinetic parameters such as the speed and the recovery coefficient are calculated, and low-cost and high-precision automatic online monitoring is achieved.

The invention provides a time-space correlation multi-camera personnel tracking method and system, and the method comprises the steps: obtaining video streams of all cameras in a scene, carrying out the frame-by-frame detection of the video streams through a detection module based on a deep learning model, and obtaining pedestrian detection samples under different cameras at the current moment and corresponding appearance features. Associating the detection sample with a historical tracking trajectory to obtain a trajectory in each single camera; and carrying out inter-camera association on the trajectory in the single camera by combining a pedestrian re-identification ReID technology and homography-based spatial constraint to obtain a complete tracking trajectory of the current frame. According to the method, in the aspect of position representation of the trajectory, 2D Kalman prediction is used in an image plane, meanwhile, the 3D space position of the trajectory is predicted and tracked, and the trajectory position can be accurately drawn and output.

The invention discloses a self-co-phase detection method for a plane diffraction spliced telescope with built-in vortex light, and belongs to the technical field of optical imaging telescopes. According to the method, an internal light source of the system is used as beacon light, so that a light beam passes through an optical system in a reverse imaging direction and is emitted in a parallel light form, and then enters the optical system again after being reflected by the front surface of a primary mirror to form a detection light beam carrying co-phase error information; and then, the detection light beam and a vortex light beam in the system generate interference on an image plane, and by acquiring and processing interference fringes in real time and extracting attitude information of the primary mirror under the combined action of forward and reverse errors, decoupling and correction of the piston and tilt errors of the spliced mirror surface can be realized, so that the error correction precision and the overall performance of the system are remarkably improved. In addition, two detectors are arranged in the system, interference fringe detection and system imaging can be achieved at the same time, a beacon light source is taken from the interior of the system, and the defect that a traditional method highly depends on external beacon light is overcome.

The invention discloses a corn detection method based on visual identification, and relates to the technical field of corn ear detection, and the method comprises the steps: collecting corn images of a corn, including an RGB image, an NIR image and a Depth image; registering the corn image based on the transformation matrix to respectively obtain a registered RGB image and a registered NIR image; creating a blank image to obtain a binary mask image; based on the binary mask image, segmenting the Depth image, registering the RGB image and registering the NIR image to respectively obtain a Depth cluster area, an RGB cluster area and an NIR cluster area; constructing an image plane corresponding to a camera visual angle under a standard attitude, and obtaining an aligned RGB image and an aligned NIR image based on the image plane, the Depth cluster area, the RGB cluster area and the NIR cluster area; and inputting the aligned RGB image and the aligned NIR image into a double-branch deep learning fusion network to obtain a detection result. The problem that the existing corn ear detection method is high in subjectivity, low in efficiency and easy to be interfered by the environment and omission and misjudgment are caused by ear attitude diversity is solved.

The invention discloses an endoscope optical system which is composed of a first lens, a steering prism, a diaphragm, a second lens, a third lens, a fourth lens, a fifth lens, a sixth lens, a seventh lens and a beam splitter prism from an object plane to an image plane, the focal power of the first lens is negative, the object side is a convex surface, and the image side is a concave surface; the focal power of the second lens is positive, the object side is a plane, and the image side is a convex surface; the object side of the third lens is a convex surface, the focal power of the fourth lens is opposite to that of the third lens, and the image side is a convex surface; the focal power of the fifth lens is positive, and the image side of the fifth lens is a convex surface; the focal power of the sixth lens is negative, the object side is a concave surface, and the image side is a concave surface; the focal power of the seventh lens is positive, the object side is a convex surface, and the image side is a convex surface; the object space numerical aperture NA of the endoscope optical system is more than 0.001 and less than 0.006, and the endoscope optical system has the advantages that lens combinations with different surface shapes and focal powers are used, and the depth of field and the axial resolution capability of an endoscope are improved by reducing the object space numerical aperture.

The invention provides a long-exit-pupil-distance broadband common-aperture composite simulation optical system, and belongs to the technical field of target scene composite analog simulation. A broadband objective lens group A, a space beam combiner group B and a long-wave infrared projection lens group D are sequentially arranged in the optical system from left to right along light, a visible light projection lens group C is located on the upper side of the space beam combiner group B, and a long-wave infrared projection lens group C is located on the lower side of the space beam combiner group B; a visible light image plane is positioned on the right side of the visible light projection lens group C; the medium-wave infrared projection lens group E is located on the lower side of the space beam combiner lens group B, the medium-wave infrared image surface is located on the lower side of the medium-wave infrared projection lens group E, the long-wave infrared image surface is located on the right side of the medium-wave infrared image surface, and the exit pupil position is located on the left side of the broadband objective lens group A; the problem that a single-channel target modulo system only adapts to simulation of imaging guidance equipment of a specific wave band and is not suitable for semi-physical simulation tests of three-mode composite imaging guidance equipment and two-mode composite imaging guidance equipment is solved.

The invention discloses a point cloud dyeing method, apparatus and device, and a readable storage medium. The method comprises the steps of obtaining a point cloud frame and a plurality of image frames; aiming at each space point of each camera device, generating an observation transformation matrix used for representing the projection movement condition of the space points on an image plane in the exposure process of the camera devices; generating a relative timestamp for indicating the imaging moment of the spatial point; based on the relative timestamp and the observation transformation matrix, generating a pixel coordinate of the spatial point projected to an image frame of the camera device, and based on the pixel coordinate, performing pixel color picking on the spatial point to obtain a pixel vector; establishing a corresponding relationship between each spatial point of different camera devices and each point cloud in the point cloud frame; and determining a color vector of the corresponding point cloud based on the pixel vector of each spatial point corresponding to the same point cloud. Visibly, according to the method, space-time alignment of the three-dimensional space points and the pixel coordinates on the image frame can be realized by constructing the observation transformation matrix and the relative timestamp, and the point cloud dyeing precision is improved.

The invention discloses a Doppler differential interferometer imaging position drift monitoring method, which solves the problem of inaccurate wind speed measurement result caused by drift of an interferometer image surface due to temperature change and the like. According to the method, periodic grooves are etched in the grating diffraction surface of the interferometer, namely, groove patterns serve as scales, the drift distance of the interferometer to be monitored is calculated, Doppler differential interferometer image surface drift caused by temperature changes can be effectively monitored, then the drift monitoring result is used for correcting the imaging position drift of the interferometer, and the drift distance of the interferometer to be monitored is calculated. Therefore, the accuracy of Doppler phase measurement is improved, the wind measurement accuracy of the interferometer is improved, and sub-pixel monitoring of the imaging position drift of the interferometer is realized.

The invention discloses a high-throughput multi-row parallel high-speed scanning high-resolution microscopic imaging device and method based on adaptive optics. A spatial light modulator is used for carrying out pixel-level regulation and control on a light beam phase to generate a strip-shaped light spot, and a special arrangement mode of a detector array is used for realizing a one-to-many relationship between a scanning line and an imaging line and realizing improvement of an imaging speed, a signal-to-noise ratio of an imaging result and a resolution ratio; a full-digital area array wavefront regulation and control method is utilized, a spatial light modulator is used for rapidly and dynamically compensating a laser wave surface according to imaging result feedback, the laser wave surface is free of distortion, and the influence of aberration on an imaging result is reduced; designing a double telecentric Fourier transform structure capable of simultaneously keeping rotational symmetry of object plane and image plane light beams, and realizing distortionless mapping of scanning light beam quality and a linear signal system; a switchable design of two scanning modes is developed, high-flux, high-resolution and high-speed light field scanning is realized, and the advantages of large visual field, high resolution and high frame rate imaging are achieved.

The invention relates to the technical field of optical design, and particularly provides an optical system polarization aberration compensation method, computer equipment and a storage medium, at least one plane mirror is additionally arranged in a to-be-compensated optical system, the plane mirror is arranged in front of an image plane of the optical system, and the spatial attitude of each plane mirror is used as a free variable to compensate the polarization aberration of the optical system. In the optional range of the spatial attitudes of the plane mirrors, the spatial attitude of each plane mirror is adjusted, and the compensated polarization aberration of the optical system meets the preset requirement by optimizing the spatial attitude of the iterative plane mirrors, so that the polarization aberration of the optical system can be compensated on the premise of not changing the wave aberration of the optical system and not occupying the degree of freedom of design. And the polarization aberration of the optical system is greatly reduced.

The invention provides a polarization camera imaging system based on aperture coding. The polarization camera imaging system comprises an imaging lens, a polarization dimension coding aperture and a polarization detector. The imaging lens comprises a front-group lens and a rear-group lens, the front-group lens is arranged in front of an aperture diaphragm of the imaging lens, and the rear-group lens is arranged behind the aperture diaphragm of the imaging lens; the polarization dimension coding aperture is arranged at an aperture diaphragm of the imaging lens, and the polarization detector is arranged at an image surface of the imaging lens; the front group of lenses consists of a plurality of lenses and is used for transmitting the collected target light information to the polarization dimension coding aperture; the polarization dimension coding aperture is used for modulating the polarization dimension of the incident light; the rear group of lenses consists of a plurality of lenses and is used for collecting target light information modulated by a polarization dimension coding aperture and transmitting the collected signal to a polarization detector; and the polarization detector is used for imaging according to the incident signal of the rear group of lenses, and the system can improve the upper limit of the dynamic range of the imaging camera by inserting a polarization dimension coding aperture at the diaphragm of the lens.