1820 results about "Imaging Signal" patented technology

The invention relates to an underwater robot navigation positioning method and system. The method comprises the following steps: S1, acquiring angular velocity and acceleration signals through an inertial measurement unit; s2, resolving a three-dimensional velocity observation value according to the beam radial velocity vector signal in combination with the angular velocity signal, and extracting environment feature point cloud data according to the acoustic image signal; s3, multi-source data time synchronization is carried out, and a fusion input signal with time-space alignment is generated; s4, constructing an adaptive factor graph optimization model, and dynamically adjusting an inertial navigation solution node based on a real-time weight coefficient; inputting the environment feature point cloud data into a closed-loop detection module to generate a loopback factor node, and adaptively correcting the weight of the node according to the feature matching degree; and S5, solving the adaptive factor graph optimization model through a nonlinear optimization algorithm. According to the underwater robot navigation positioning method and system, the problem that the fusion positioning precision of a multi-source heterogeneous sensor is insufficient in an underwater GPS-free environment can be solved.

The present invention relates to the technical field of cross-modal image signal reconstruction. Disclosed is a cross-modal joint source-channel coding and decoding method adaptable to changeable scenarios. The method comprises: first designing a Transformer encoder-based cross-modal channel coding and decoding optimization solution, so as to achieve the performance improvement and robustness of a channel encoder and a channel decoder; then designing a cross-modal source coding and decoding optimization solution for haptic-to-image generation based on a latent diffusion model, so that under an image signal loss scenario, haptic information is used to guide image generation; and finally, incorporating transfer learning technology, so as to reduce additional training costs caused by a system facing changeable cross-modal communication scenarios such as a changeable channel signal-to-noise ratio and different transmission tasks. Under cross-modal changeable communication scenarios, the joint source-channel coding and decoding method provided in the present invention can solve the problems of the inability of a receiving end to well complete image reconstruction, and additional model training costs caused by changeable channel environments and scenarios.

The invention relates to the field of image data processing, and discloses a texture preserving type image denoising and enhancing method based on a generative adversarial network, which comprises the following steps: acquiring an original image signal, and calculating low-frequency sub-band data and high-frequency sub-band data by using discrete wavelet transform; calculating the gradient magnitude of the low-frequency sub-band data to generate a structural significance gradient map; establishing a reverse mapping relation based on the structure saliency gradient map, and generating a spatial self-adaptive dynamic gating threshold; performing statistical gating on the high-frequency sub-band data by using the dynamic gating threshold to generate a high-pass gain coefficient and a low-pass suppression coefficient; according to the method, cross-band modulation logic of the structure flow to the texture flow is established, so that the problem that weak texture signals are easy to lose under non-uniform illumination is solved, and non-structured noise filtering and structured micro texture restoration are realized on the premise of not depending on semantic tags.

A system and method are disclosed for low-light image enhancement using hierarchical adaptive wavelet decomposition with cross-scale feature fusion. The system analyzes a raw input image to determine image characteristics and preprocessing parameters. A hierarchical adaptive wavelet decomposition process creates a variable-depth decomposition tree comprising frequency domain nodes, with decomposition depth determined by local image complexity. Cross-scale feature fusion implements attention mechanisms between nodes at different decomposition levels, enabling bidirectional information flow across scales. A dynamic network pool allocates specialized neural networks to process nodes based on their frequency characteristics, with weight sharing between similar nodes for efficiency. An adaptive reconstruction engine traverses the decomposition tree using learned filters and multi-scale residual learning to produce an enhanced image. The hierarchical approach enables superior low-light image enhancement by allocating computational resources based on content complexity, achieving better quality than fixed decomposition methods while maintaining compatibility with existing image signal processing pipelines.

The invention provides an offshore wind turbine generator fault diagnosis method and system based on multi-source sensor data fusion. The method comprises the steps that a vibration signal from at least one component of a wind turbine generator is acquired through a vibration sensor; performing time-frequency conversion on the vibration signal by applying synchronous compression wavelet transform to obtain time-frequency representation of the vibration signal; when the reconstruction error exceeds a preset threshold value, it is judged that an abnormal event exists in the vibration signal; obtaining the position of a part corresponding to the abnormal event; starting an image sensor and an acoustic sensor according to the position of the component, and acquiring an image signal and a sound signal of the component according to the image sensor and the acoustic sensor; according to the DS evidence theory, the vibration signal, the image signal and the sound signal, obtaining the confidence of the fault type; the fault type of the component is judged according to the maximum confidence allocation principle, high-resolution time-frequency analysis can be achieved through synchronous compression wavelet transform (SST), and the fault feature identification degree is improved in combination with the self-encoding neural network and the D-S evidence theory.

The invention relates to an unmanned aerial vehicle inspection method and system based on an overhead transmission line, and the method comprises the steps: S1, generating an unmanned aerial vehicle three-dimensional space coordinate signal, and outputting a position correction signal based on a tower topology database; s2, in response to the position correction signal, controlling a multispectral sensing module to synchronously acquire a visible light image signal, an infrared temperature signal and a laser radar point cloud signal of the line; s3, inputting the visible light image signal into a defect identification model to generate a first defect feature signal; s4, fusing the first defect characteristic signal and the second defect characteristic signal to form a cross-modal diagnosis signal, and triggering a defect classification decision signal; and S5, classifying decision signals and cross-modal diagnosis signals according to defects. According to the air quality intelligent monitoring method and system based on sensing data feedback, the problems of inaccuracy in routing inspection positioning, defect missing detection and insufficient endurance in a complex environment can be solved.

The invention relates to the technical field of power transmission line detection, and provides a high-voltage overhead power transmission line insulator string detection device and a control method thereof. Comprising an unmanned aerial vehicle body, and an airborne data transmission module, an airborne insulator detection module and an image acquisition and analysis module which are carried on the unmanned aerial vehicle body, the image acquisition and analysis module is used for acquiring an image signal of the insulator string and analyzing the image signal so as to output a position control signal of the unmanned aerial vehicle and an angle control signal of the airborne insulator detection module; the unmanned aerial vehicle body flies to a specified position based on the position control signal; the airborne insulator detection module is used for rotating to a specified angle based on the angle control signal and detecting an insulator string; and the airborne data transmission module is used for receiving the detection data sent by the airborne insulator detection module and determining the health state of the insulator chain based on the detection data. Zero-value insulator live-line detection of a full-voltage-class full-string type insulator string of a power transmission line can be realized.

According to embodiments, a system for imaging a blood flow in a region of interest of a patient includes: a display configured to display an image; a processor configured to execute the instructions to: obtain ultrasound imaging data based on an imaging signal; select the region of interest in the ultrasound image data; determine at least one characteristic of a blood flow in the region of interest; generate an animation indicating the at least one characteristic of the blood flow in the region of interest, wherein the animation indicates the blood flow during a single time slot; and control the display to display a static image including the region of interest and the animation within the region of interest.

The invention relates to a naked eye 3D binocular image acquisition and real-time processing system based on hardware synchronous triggering, and belongs to the technical field of image processing and three-dimensional display. According to the system, a hardware synchronous triggering mechanism is adopted, a time sequence synchronous control unit is used for sending a synchronous pulse signal to a binocular image sensor, and strict synchronization of left and right viewpoint image acquisition is ensured. The image signal processing unit processes collected original data, the stereo parallax correction module performs epipolar correction, and the sub-pixel interleaving module generates a composite view frame according to grating parameters of the display terminal. The system realizes high-speed data transmission through a double-buffer direct memory access DMA mechanism. The problems of visual tearing and weak stereoscopic impression caused by asynchronous binocular image acquisition in the prior art are solved, nanosecond-level synchronization precision is realized, optical crosstalk is reduced, and smoothness and comfort of stereoscopic display are ensured.

The invention discloses a farmland soil moisture content real-time surveying system and method based on unmanned aerial vehicle multispectral imaging. The method comprises the steps that multispectral sensor parameters are configured, and an unmanned aerial vehicle flight scanning path is planned; a space coordinate system and time synchronization mechanism is established, and high-precision positioning and time synchronization are achieved; collecting and calibrating visible light, near-infrared and short-wave infrared original image data to form a spectral signal set; calculating an image signal-to-noise ratio, screening a low-quality image, and executing noise suppression; extracting timestamp information from the suppressed image, performing spatial positioning, and establishing a spatial corresponding relation database; calculating time synchronization precision and performing image correction; evaluating the spatial resolution according to the distortion coefficient; calculating a comprehensive quality parameter, comparing the comprehensive quality parameter with a threshold value, and obtaining a soil moisture content distribution parameter when a condition is met; a farmland moisture state map is generated, partition marking is carried out according to a multi-level standard, a monitoring result is output, and high-precision and real-time monitoring of the farmland soil moisture content is achieved.

The invention relates to the field of textile detection, and discloses a fabric flame retardance analysis method based on infrared thermal imaging sensing data, which comprises the following steps: performing non-contact temperature measurement on a fabric sample in a controlled heat shock disturbance field, acquiring an infrared imaging signal sequence, and performing energy projection rearrangement on the infrared imaging signal sequence; based on the discontinuous change of the energy flow density in the primary thermal behavior field, establishing a boundary disturbance model of a local overheating region, and comparing the morphological difference between a thermal expansion path and a radiation energy attenuation region; mapping the heat potential difference of each region in the critical response diagram into an energy constraint state inside the material, and deducing time bias distribution of energy conduction; introducing a spectrum equalization function under time offset distribution, and executing asymmetric compensation on local abnormal points of the infrared response data; and based on the decomposition threshold dynamic trajectory, calculating a flame-retardant response equilibrium rate and an energy flow retention rate, and forming a flame-retardant performance evaluation index. The method has the advantage of improving the accuracy of flame retardant detection.

The invention discloses an ultra-wide-spectrum endoscopic imaging device capable of being used for short-wave infrared fluorescence imaging, which is used for in-vivo minimally invasive imaging and comprises an illumination module, a wide-spectrum image transmission module, an imaging module and an image processing module. The illumination module consists of a light source and a light guide optical fiber, and is used for generating illumination light from ultraviolet to short wave infrared band and transmitting the illumination light to the wide-spectrum image transmission module; the wide-spectrum image transmission module consists of a few-interface optical imaging channel and a light guide illumination channel, and is used for illuminating an imaging target, exciting target fluorescence and collecting image signals from ultraviolet to short-wave infrared bands; the imaging module is composed of an optical filter and an imaging camera, and the imaging camera can be a wide spectral response image sensor or can be formed by combining cameras working in different wavebands and is used for converting optical images in different wavebands into image data; and the image processing module is used for registering and fusing image data of different wavebands in real time and displaying the image data.

The invention relates to a high-signal-to-noise-ratio ultrasonic imaging method and device for internal defects of a curved surface component, a medium and a product, and belongs to the technical field of ultrasonic imaging. According to the method, a linear array ultrasonic probe is adopted to carry out single-time ultrasonic excitation on a curved surface component, a full-matrix echo signal is obtained, first arrival time extraction is carried out on the collected signal, an ultrasonic incident angle is estimated, and discrete coordinates of the surface of the component are obtained; the method comprises the following steps of: fitting a curved surface model, constructing an equivalent virtual array model, calculating transmitting and receiving delay time of each pixel point, realizing initial full-focusing beam forming of signals, estimating an expected signal variance and a noise variance based on maximum likelihood estimation, constructing an initial coherent beam forming machine and performing iterative updating, and finally forming a beam. And taking the coherent beam synthesizer obtained by iteration as a weighting factor, acting on an initial beam synthesis signal for weighting, and completing image reconstruction. The method has the advantages of being high in calculation efficiency, low in system overhead, high in imaging signal-to-noise ratio and the like, and accurate imaging can be achieved in a curved surface structure scene.

The embodiment of the invention discloses a scanning NV probe microscope which comprises an atomic force microscopy system used for detecting surface topography information of a sample and an optical detection magnetic resonance system used for detecting surface magnetic field distribution information of the sample, and the atomic force microscopy system comprises a vibration arm and a diamond probe. The optical detection magnetic resonance system comprises an NV color center, a transition excitation light path and a fluorescence detection light path; a sample to be scanned and the transition excitation light path are respectively positioned on two opposite sides of the diamond probe, and the transition excitation light path and the fluorescence detection light path are positioned on the same side of the diamond probe; a first metal coating film is arranged on one side, close to the sample, of the diamond probe and is used for blocking surface fluorescence of the sample. According to the scanning NV probe microscope provided by the embodiment of the invention, the metal coating is arranged at the bottom of the diamond probe to block stray fluorescence from the surface of the sample, so that the problems of low magnetic field imaging signal-to-noise ratio and limited measurement precision of the existing scanning NV probe microscope are solved.

A high-order driving auxiliary lane changing trajectory planning method for an intelligent vehicle comprises the steps that laser radar and camera data are obtained, and feature vectors of obstacles are extracted after the data are processed by an ISP at the front end of a chip of the intelligent vehicle; constructing a spatio-temporal joint attention network model, inputting the feature vector of the obstacle into the spatio-temporal joint attention network model, calculating an interaction weight between the vehicle and the obstacle through a self-attention mechanism, and synchronously outputting predicted trajectory distribution of the obstacle and a candidate planning trajectory cluster of the vehicle; introducing a dynamic game in the game theory, and constructing a comprehensive cost function in combination with the interaction weight to obtain a screened track; and taking the screened trajectory as an initial value, inputting the initial value into a rear-end quadratic programming optimizer on the premise of meeting vehicle dynamics constraints, carrying out numerical optimization solution, searching an optimal programming sequence, and finally finishing lane changing trajectory planning. According to the invention, the interactive perception capability and riding comfort of the intelligent vehicle in a complex traffic scene can be improved.

An endoscopic imaging system for use in a light deficient environment includes an imaging device having a tube, one or more image sensors, and a lens assembly including at least one optical elements that corresponds to the one or more image sensors. The endoscopic system includes a display for a user to visualize a scene and an image signal processing controller. The endoscopic system includes a light engine having an illumination source generating one or more pulses of electromagnetic radiation and a lumen transmitting one or more pulses of electromagnetic radiation to a distal tip of an endoscope.

The invention discloses an endoscope image processing method based on oxyhemoglobin saturation and multiple central wavelengths, and relates to the field of medical image processing.The method comprises the steps that a first initial image signal, a second initial image signal, a third initial image signal and a fourth initial image signal are obtained; calculating oxyhemoglobin concentration information of the target part according to the second initial image signal and the third initial image signal; calculating deoxidized hemoglobin concentration information of the target part according to the second initial image signal and the fourth initial image signal; calculating the oxyhemoglobin saturation of the target part according to the oxyhemoglobin concentration information and the deoxidized hemoglobin concentration information; performing brightness enhancement on the second initial image signal based on the oxyhemoglobin saturation to obtain a second enhanced image signal; and generating a target image according to the second enhanced image signal, the first initial image signal and the third initial image signal, wherein the target image is used for identifying the bleeding position of the target part.

The invention discloses a liquid crystal display device for improving contrast based on movable light guide lattice points and a light guide layer and a control method of the liquid crystal display device. The device comprises a backlight module, a dynamic light guide layer, a liquid crystal display panel and a control system. The dynamic light guide layer is packaged by two transparent substrates to form a sealed cavity, the cavity is filled with transparent base liquid and movable micro units with different refractive indexes, and transparent electrode arrays are arranged on the inner surfaces of the substrates. The control system controls the electrode array to generate a corresponding electric field according to brightness and darkness distribution of an input image signal, drives the micro-units to move in the base liquid and gather to the position below an image brightness field area so as to enhance light output, and meanwhile enables the micro-units to be dispersed below a dark field area so as to reduce light leakage. According to the invention, a static light guide structure is changed into a dynamic programming system, and the real-time pixel-level matching of backlight distribution and display content is realized, so that the contrast ratio is remarkably improved, the halo is inhibited, and the power consumption is reduced. The invention also protects the core component of the dynamic light guide layer and the corresponding control method.

A display device includes a pixel unit that includes a plurality of pixels, a compensator configured to receive sensing data from the pixel unit in a sensing period and that detects and compensates for a characteristic of the pixels, and a timing controller configured to convert an image signal received from an outside into image data.

The invention relates to the technical field of smart home control, and particularly discloses a smart home central control system and method based on multi-mode perception, and the system comprises the steps: synchronously collecting a voice audio signal, a gesture image signal, an infrared thermal imaging signal and a millimeter wave radar signal through a plurality of groups of sensors; performing blind source separation processing on the voice and gesture signals, extracting a voice command component and a gesture action component which are independent in statistics, and performing space-time alignment and Kalman filtering fusion on the infrared and radar signals to generate a dynamic environment sensing graph; voice intention features, gesture track features and environment anomaly features are extracted through Mel frequency cepstrum coefficient analysis, skeleton key point tracking and multi-level convolution processing; constructing a three-dimensional decision matrix based on the features, performing weighted evaluation through a fuzzy logic rule base to generate a control instruction priority sequence, and dynamically adjusting an equipment operation mode according to the priority; according to the invention, the problems of control conflict and response delay caused by multi-mode signal coupling are solved.

The invention belongs to the field of image processing, and provides a projection image automatic correction method and system based on deep learning, and the method comprises the steps: controlling a projector to output a preset test image; acquiring a first image of a user at a viewing angle by the mobile terminal; acquiring a second image at a projection angle by a shooting device of the projector; extracting features and predicting adjustment parameters for projection correction based on a projection image correction model of deep learning; the adjustment parameters are issued to the projector through a network; and performing pre-distortion processing on an image signal to be projected based on the geometric mapping parameter, and performing pixel-level adjustment of brightness and color based on the compensation parameter to generate a corrected projection output image. According to the method, the usability and accuracy of projection image correction can be improved.

An image capturing apparatus for capturing an object and generate an image, displaying the image, performing signal processing for the image, and accepting an input from a user, wherein the image is displayed with a vectorscope superimposed thereon, the vectorscope indicating a distribution of color components included in the image based on a hue and a color density and an index for specifying a range of a skin color region in the image, a display position of the index on the vectorscope is specified based on the hue and the color density values, and a size of the index is specified by the range of the skin color region value, and processing is performed for decreasing a detail level of an image signal of the image having a color component included in the index.

The invention provides a polarization hyperspectral water quality monitoring system and method, and the system comprises a tower footing polarization hyperspectral imaging module which is disposed on a building beside a to-be-detected water area, and carries out the area array staring scanning of the to-be-detected water area through a polarization hyperspectral imager, so as to obtain a water body polarization hyperspectral image signal of the to-be-detected water area; the image spectral data processing module is used for deducting dark current and spurious signals from the water body polarization hyperspectral image signals, and calculating the water body spectral reflectivity of the water area to be measured according to the water body polarization hyperspectral image signals by combining a gray value and reflectivity relation model constructed by using the hyperspectral image signals of the gray scale calibration plate; and the water quality parameter spatial distribution inversion module is used for performing inversion on the to-be-detected water quality parameters of the to-be-detected water area according to a pre-constructed water quality parameter inversion model and the water body spectral reflectivity. According to the technical scheme, the integration level is high, the automation degree is high, rapid deployment can be achieved, and all-day continuous unattended monitoring can be achieved.

The present application provides an information processing device and method, and a computer-readable storage medium. The information processing device comprises a processing circuit which is configured to: generate a saliency map of a sample image on the basis of a predetermined model which processes a task for the sample image, wherein the saliency map reflects the degree of attention to objects at different positions in the sample image when the predetermined model processes the task; and adjust, on the basis of the saliency map and the labeling area in the sample image, the parameters of the image signal processor which generates the sample image, such that the difference between the task processing result and the labeling value of the sample image meets a preset condition.

Systems and techniques are described for image signal processor motion detection. In various examples, first image data including pixel values may be generated, where each pixel value is associated with a respective color tag of a color filter array. A first set of the pixel values corresponding to a first block may be determined. A second set of pixel values may be determined based on a respective pixel value of the first set and the respective color tag associated with that respective pixel value. A first intensity value associated with the first block may be determined based on the second set of pixel values. A second intensity value associated with a reference block may be determined. A comparison value representing a difference between the first intensity value and the second intensity value may be determined. A signal indicating detected motion may be sent based on the comparison value.

The invention provides a photoelectric pod tracking method and system for an unmanned aerial vehicle platform. The photoelectric pod tracking method comprises the steps of collecting multi-mode sensor original data of the unmanned aerial vehicle platform in a target scene through a photoelectric pod; performing image processing on the original data of the multi-modal sensor by using a self-adaptive image signal processing algorithm based on a deep reinforcement learning model to obtain an optimized multi-modal image; performing semantic feature extraction on the optimized multi-modal image by using a double-flow neural network to obtain deep multi-semantic association features, and performing fusion processing on the deep multi-semantic association features to obtain a unified feature map in a target scene; based on the unified feature map, using a Transform model to track a target of the unmanned aerial vehicle platform in the target scene to obtain real-time coordinate information of the target; when the target is tracked, self-adaptive image processing is carried out based on the original data of the multi-mode sensor, and stable and efficient tracking of the target in the target scene by the photoelectric pod is facilitated.

This disclosure provides systems, methods, and devices for image signal processing that support adjusting a Bokeh effect in image data. In a first aspect, a method of image processing includes receiving a first user input specifying a first depth of focus. A camera is configured with a first aperture size of a plurality of aperture sizes of the camera that is nearest a second aperture size that corresponds to the first depth of focus. The first aperture size is smaller than the second aperture size. Image data representing a scene is received that is captured with the first aperture size of the camera. First modified image data is determined by applying a first blur kernel to the image data. The first modified image data represents the scene at the depth of focus corresponding to the second aperture size. Other aspects and features are also claimed and described.

The invention discloses an assembly type steel structure connection quality detection method and system, and relates to the technical field of steel structure assembly and intelligent detection, and the method comprises the steps: collecting node vibration, strain and image signals, carrying out the preprocessing, and constructing a detection data set; calculating characteristic parameters of connection of the bolt and the weld joint based on the detection data set, and outputting a comparability index through normalized mapping; performing weighted synthesis on the comparability index of the bolt connection index and the weld joint connection, generating a node quality score, and establishing a grading threshold parameter; and calling a node quality score and a grading threshold parameter, executing a segmentation judgment function to output a node quality grade, and executing data verification on a segmentation judgment function result. According to the method, multi-source signals are synchronously collected and subjected to standardized processing, the connection characteristics of bolts and welding seams are fused, a unified quality scoring and grading judgment system is established, and quantitative and traceable evaluation of the connection quality of the fabricated steel structure is achieved.

The invention provides a multi-modal fusion unmanned aerial vehicle identification method and system, and the method comprises the steps: obtaining a radio signal, an image signal and a sound signal of an unmanned aerial vehicle; performing feature extraction on the radio signal based on a blind source separation algorithm and adaptive filtering to obtain radio features; performing feature extraction on the image signal based on image super-resolution reconstruction and a double-flow feature extraction network to obtain image features; performing feature extraction on the sound signal based on spectral analysis and harmonic feature extraction to obtain an audio feature; fusing the radio feature, the image feature and the audio feature to form a multi-modal fusion feature; and performing identification based on the multi-modal fusion features to obtain an unmanned aerial vehicle category identification result. By adopting the scheme, the accuracy, reliability and environmental adaptability of unmanned aerial vehicle identification can be remarkably improved.

The invention discloses a multi-sensor fusion target scoring system high-precision positioning method, and relates to the technical field of target scoring positioning, and the method comprises the following steps: building a transient interference recognition channel based on the electromagnetic response of a shock wave sensor, obtaining the electromagnetic disturbance of the bullet hit front edge, and generating an interference time sequence; performing delay triggering on the image sensor according to the interference time sequence, and avoiding an interference peak value to form a safe exposure time period; performing charge pre-release on the image acquisition chain before safe exposure; carrying out synchronous compensation on the shock wave signal based on energy distribution of charge pre-release, so that the shock wave signal and image energy response are symmetrical and mutually stable in a time domain; and dynamic shielding control is carried out on a space coupling path between the two types of sensors by utilizing an energy balance region formed in the mutual stable state. Through energy symmetric compensation and dynamic shielding control of shock waves and image signals, time-space separation and synchronous mutual stability of the signals are achieved, and high precision and stability of target scoring positioning under high-energy shooting are ensured.