366 results about "Background light" patented technology

Disclosed in the present invention is a salient contour matching-based method for target measurement in a severe imaging environment. The method specifically comprises: (1) acquiring a binocular image of a target; (2) establishing a global-local joint constraint-based background light estimation model, and removing a scattering effect of a medium in an imaging environment to obtain a restored left eye image and a restored right eye image; (3) learning an original image, and on the basis of a residual between a network reconstructed image and the original image, obtaining target localization prediction maps of the left eye image and the right eye image; and (4) respectively extracting contour lines of the target in the left eye image and the right eye image, constructing feature matching descriptors of contour points, performing stereo matching on the two sets of contour lines by minimizing matching cost, and performing three-dimensional reconstruction on the contour lines in light of calibrated intrinsic and extrinsic parameters to complete the measurement of a key size. According to the present invention, the key sizes of different targets in a severe environment can be accurately measured, thereby providing an effective solution for the problem of measuring the sizes of targets in a severe environment.

The invention discloses a transformer oil leakage detection method and device based on polarization-ultraviolet fusion imaging, and the device comprises a housing, a support, a camera, an environment induction device, an overall controller, a power supply, a polaroid rotating wheel assembly, a lens seat assembly, and an image processor. And the motor driver, the illumination intensity sensor, the ultraviolet irradiance sensor, the image processor and the power supply are electrically connected with the integral controller respectively. According to the invention, a multi-angle polarization image and a non-polarization image in the same field of view can be acquired, and then polarization characteristics contained in an oil stain fluorescence signal are extracted and effectively distinguished from non-polarization characteristics of background light; in the daytime mode, the transformer oil leakage detection device can identify a target area with relatively high polarization intensity, and through image fusion enhancement processing, non-target background signals are significantly suppressed, and the fluorescence significance of an oil leakage characteristic area is improved.

The invention discloses an underwater image de-scattering method, system and device for scattering field decoupling in the technical field of underwater optical imaging and computer vision, and the method comprises the steps: calculating an intensity graph and a scene linear polarization degree graph according to an obtained multi-scale underwater image; according to the intensity image, performing image signal decomposition by using a dynamically constrained background light separation model to obtain a background scattering component and a target feature component; according to the scene linear polarization degree map and the background scattering component, calculating fusion transmissivity according to a non-linear optical transmission equation; carrying out noise suppression processing on the fusion transmissivity by adopting a double-constraint optimization architecture to obtain the fusion transmissivity subjected to noise suppression processing; and performing image reconstruction through a reverse optical propagation model according to the fusion transmissivity and the target feature component subjected to noise suppression processing to obtain a scattering-removed underwater image. The method effectively breaks through the dependence of a traditional method on the uniform hypothesis of a scattered field, and provides high-precision visual restoration support for an underwater detection task.

The invention discloses an LED (Light Emitting Diode) energy-saving street lamp system self-adaptive to an ambient light effect and an illumination adjusting method thereof, and belongs to the technical field of novel illumination control and green energy conservation. The system comprises a light environment sensing module, a traffic flow monitoring module, an LED driving power supply and an electroluminescent illumination module composed of a plurality of light emitting diodes. The main control module is configured to execute active lighting effect decoupling logic, namely, when the electroluminescent lighting module keeps steady-state lighting, the driving power supply is controlled to inject a micro-disturbance modulation signal which cannot be perceived by human vision into output current, and illuminance response data of the light environment perception module are synchronously collected; the road surface reflectivity coupling coefficient is obtained in real time by calculating the change ratio of the response data to the modulation signal, then the reflected light component excited by the street lamp itself is accurately removed from the total illumination value, and the pure environment background illumination is decoupled. The problems of misoperation and energy waste caused by self-luminous interference of a traditional light-operated street lamp are solved.

Systems and methods are provided for time resolution of signals produced by the emission of energy. More particularly, systems and methods are provided for measuring distance using photons propagating in a scattering medium to produce multi-dimensional, measurements of objects in a media and / or the media itself by virtue of the character of light spatially scattered and absorbed in the media resulting from the transmission of light into the media, such transmitted light having some temporal character that distinguishes it from background light, e.g., ambient sources. A method for obtaining terrestrial LiDAR data generally includes: providing a LiDAR system moving traverse to a ground canopy; emitting light pulses from the LiDAR system toward the ground canopy and terrain such that the light pulses reflect therefrom; and receiving the reflected light pulses at the LiDAR system; wherein the LiDAR system includes a monolithic module comprising a photonic device, a sampling module, a digitizing module, and a readout integrated circuit (ROIC).

The invention discloses a space-time fringe analysis method based on physical prior guidance. The method comprises the following steps: firstly, acquiring a stripe sequence taking a target frame as a center, and separating background light through a background estimation network to obtain background light intensity; then, under the assumption of constant brightness and small displacement, an optical flow pixel alignment module is used for estimating inter-frame optical flow, and sub-pixel-level registration is carried out on the subsequences; and finally, inputting the alignment sequence into Attention U-Net with an attention mechanism to carry out space-time phase demodulation, and outputting a target frame phase. And then phase unwrapping is carried out, and three-dimensional reconstruction is completed in combination with system calibration parameters. In the training stage, a space-time consistency loss function and a frequency domain consistency loss function are introduced to improve the generalization ability. The method has high phase demodulation precision and time sequence stability in a low signal-to-noise ratio and fast motion scene, and is suitable for high-speed three-dimensional measurement engineering application.

The invention discloses an underwater image degradation diffusion self-supervised enhancement model and a building and training method, and relates to the technical field of underwater image enhancement. The invention provides an underwater image degradation diffusion self-supervised enhancement model and a building and training method for the problem of target detection performance reduction caused by underwater image quality degradation, the model built by the method is combined with the differential thought of a Koschmieder illumination scattering degradation model and a diffusion model, the degradation process of a real underwater environment is simulated, and the target detection performance is improved. Self-supervised training data is generated, dependence of a traditional method on manual annotation data is avoided, image features are extracted through a ResNet50 backbone network, global background light and transmission rate are predicted in parallel, a clear image is reversely recovered by using a physical formula, transmission rate consistency loss, background light consistency loss and reconstruction loss are also proposed, an unsupervised optimization target is constructed, and the self-supervised training data is obtained. And the accuracy and stability of model training are ensured.

The invention discloses a ranging communication fusion miniaturized system and method based on single photon detection. The system adopts a time division multiplexing common-path structure, and a ranging pulse sequence and a communication pulse sequence are sequentially transmitted in the same detection period to form a PPM modulation laser pulse chain. A single-photon detector is adopted to receive signals, background light interference is suppressed by combining a narrow-band filter and a time gating technology, and the type and boundary of a pulse sequence are identified through a signal demodulation and discrimination module. When the distance measurement pulse sequence is identified, the distance measurement path realizes distance measurement based on the round-trip time of the distance measurement pulse in the period; when a communication pulse sequence is identified, the communication path demodulates the PPM communication data. The method effectively decouples the contradiction between the distance measurement fuzzy and the communication rate, supports communication pulse high repetition frequency modulation while realizing non-fuzzy distance measurement, improves the distance measurement precision and the communication rate, and is suitable for free space communication, mobile robot platforms and other application scenes.

A visible light communication apparatus comprising: multiple sources, at least one source being a light source configured to transmit a data signal; and a receiver comprising a polarizer, operating in a visible light spectrum, the receiver configured to receive visible light energy from the one or more sources; the polarizer configured to filter multiple noise signals and allow the data signal to pass through to the receiver. Allows more signal light than background light to reach the sensor, the polarizer improves signal to noise ratio for outdoor visible light communication.

The invention discloses a gas leakage detection imaging device and method based on a single photon detection technology, and belongs to the technical field of gas detection and imaging. Aiming at the limitation problems of the existing gas leakage detection technology in the aspects of sensitivity, response speed, space imaging capability and anti-interference capability, nanosecond modulation control and synchronous photon counting are realized by utilizing an FPGA (Field Programmable Gate Array) through a visual gas detection imaging device combining an SPAD (Single Program Amplifier) array detector and a WMS modulation-demodulation mechanism; and the second harmonic of the absorption signal is further extracted by combining digital phase-locked amplification, so that gas leakage three-dimensional imaging with high spatial resolution, ppb-level sensitivity, strong background suppression capability and high time response is realized. The system has the advantages of high detection sensitivity, real-time imaging capability with high spatial resolution, high background light interference resistance and high signal-to-noise ratio, the demodulation method is novel, and the modular design has multi-gas compatibility and system expansibility.

The invention discloses a scattering characteristic adaptive polarization imaging non-uniform fog transmission method, which comprises the following steps of: acquiring polarization images at different angles, and calculating Stokes vectors, linear polarization degrees and dual-channel polarization intensity images of the images; constructing a non-uniform fog scattering feature, and estimating a dual-channel non-uniform scattering intensity image; estimating background light at infinity, and calculating a dual-channel polarization intensity transmissivity image; constructing an attenuation matrix of the polarization dual-channel variable-scale degradation model; a polarization dual-channel variable-scale degradation imaging model is constructed, and preliminary restoration of a dual-channel non-uniform fog scene is solved; and iterating the optimal polarization variable-scale degradation matrix to obtain a final restored image of the fogless scene. According to the scattering feature self-adaptive polarization imaging non-uniform fog transmitting method, the problems of overexposure and the like caused by target polarization information loss in a non-uniform fog scene are solved, complete removal of global non-uniform fog of the scene is realized, and target scene information is restored more clearly.

The invention discloses a deep learning method for uniform background light and shadow based on a Transform model. The method comprises the steps that an input image and a corresponding portrait main body mask are acquired, and the input image comprises an area with uneven background light and shadow; preprocessing the input image and the portrait main body mask, including image standardization and feature fusion, to obtain a fused feature map; based on a patch segmentation method, converting the fusion feature map into sequence features; encoding the sequence features to output enhanced sequence features, modeling a light and shadow distribution dependency relationship of full image pixels through a global attention mechanism, and distinguishing portrait main body features and background features based on the portrait main body mask; and based on the inverse logic of patch segmentation, recovering the enhanced sequence features into a spatial feature graph and the like. According to the method, semantic mask prior, global context modeling and adaptive residual correction are organically integrated, and a solution is provided for solving the core problem in background light and shadow homogenization.

The invention provides a physical guidance-based sparse coding-driven underwater image enhancement method, a program, equipment and a storage medium. The method comprises the following steps: constructing a physical guidance preprocessing method based on a Jaffe-McGammy model, and adaptively estimating an underwater transmission image and background light to realize preliminary degradation recovery; elastic regularization sparse coding is adopted, and through sparsity and smoothness combined constraint, salient structure information such as edges and textures of the image is effectively extracted, so that the image definition and the detail recovery capability are enhanced; cross-channel attention fusion is adopted, a multi-scale context modeling and channel interaction mechanism is introduced, and a physical degradation graph is combined for guidance, so that color consistency and semantic expression integrity between channels are remarkably improved, and the problems of color shift and information loss in an existing method are solved. According to the method, through joint optimization of multiple loss functions, the constructed underwater image enhancement network keeps the illumination accuracy, texture continuity and structural integrity of the image in multiple dimensions at the same time.

According to the chemical material detection method and system based on deep learning provided by the invention, the online adaptive training generative adversarial network BR-GAN is introduced, and the generator can dynamically learn background optical feature mapping under the fine tuning condition of production process parameters; meanwhile, a multi-layer convolution discriminator is used for recognizing time correlation of background optical features, so that a defect-free background reconstruction image matched with the current production condition can be generated, and a difference image is generated by calculating pixel-level residual errors and feature-level attention differences of a real-time image and the reconstruction background; microscopic bubble signals are effectively separated from complex backgrounds changing along with technological parameters, and the effect of accurately detecting microscopic bubbles is achieved.

The utility model relates to the technical field of biological detection, and discloses a bioluminescence detector which comprises a bottom plate, a reagent rack and a luminescence detection module, the reagent rack and the luminescence detection module are arranged on the bottom plate, the reagent rack is connected with a kit in a sliding manner, a light filtering assembly is arranged above the kit, the light filtering assembly is provided with a plurality of light filters for selecting light waves, and the light filtering assembly is connected with the luminescence detection module. The luminous detection module detects an optical signal in the kit through the optical filter; the whole structure is compact, optical signals of non-target wavelengths can be removed and background light interference can be reduced by using the optical filters, so that the purity of the detection signals is improved, the light emitting detection module can detect the optical signals of the target wavelengths in a more targeted manner, and the accuracy of the detection result is enhanced; the appropriate filtering wave band can be selected according to different types of chemical agent reactions to meet different detection requirements, the application range of the detector is expanded, and the detector can be suitable for various bioluminescence reactions.

The invention relates to the technical field of image processing, and discloses a method and system for switching backgrounds in batches to form a new image based on a convolutional neural network, and the method comprises the steps: carrying out the analysis of a cartoon image, obtaining a foreground segmentation mask and a foreground material feature tensor, carrying out the analysis of a target background image, and obtaining a background illumination feature vector; dynamic light and shadow interaction between a cartoon foreground and a new background is simulated by constructing a double-medium light interaction field, fine fusion of an edge region is realized in combination with an edge transmission matrix, the problem of visual splitting caused by light and shadow interaction deficiency in background switching of a traditional convolutional neural network is solved, and meanwhile, through a light and shadow residual image correction mechanism, the dynamic light and shadow interaction between the cartoon foreground and the new background is corrected. The illumination consistency is further optimized, the fusion matching degree of the cartoon image and various real or virtual scenes is remarkably improved, the diversified marketing scenes can be efficiently adapted through a batch processing mode, and the batch replacement requirement is met while the visual naturalness is guaranteed.

The invention relates to the technical field of computer vision, and discloses a dynamic four-dimensional content generation method and device based on a single image, equipment and a medium, and the method comprises the steps: generating a corresponding multi-view image set based on an input single static image; constructing a static three-dimensional scene representation model based on the multi-view image set; converting the static three-dimensional scene representation model into a dynamic four-dimensional scene representation model; performing time consistency optimization processing on the dynamic four-dimensional scene representation model to generate a dynamic frame sequence coherent in time dimension; and background illumination controllable editing processing is carried out on the dynamic frame sequence after time consistency optimization processing, and final editable dynamic four-dimensional content is generated. According to the method and the device, the three-dimensional model is constructed by utilizing the multi-view image set and is further converted into the dynamic four-dimensional model, so that the problems of insufficient multi-view image continuity and unstable dynamic details in time dimension in the prior art are solved, and the reality sense of dynamic contents and the user experience are improved.

The invention discloses an image processing system and method suitable for a turbid water area, and belongs to the technical field of image processing. The system comprises an underwater camera component for collecting original image data of a turbid water area in real time and an embedded image processing unit. The embedded image processing unit comprises a preprocessing module used for carrying out noise suppression and image calibration processing on original image data, and a physical parameter estimation module used for estimating environment background light intensity of a current water area, a water body attenuation coefficient and a distance map of an object in a scene and calculating initial transmissivity. The scattering correction module is used for removing back scattering and preliminarily compensating a color channel based on a physical imaging model in combination with physical parameters, and the deep learning enhancement module is used for improving image local contrast, adjusting brightness and finely correcting colors by adopting a lightweight deep convolutional neural network. According to the image processing system and method suitable for the turbid water area, the image definition and color of the turbid water area can be improved, the real-time performance is high, and the system and method are suitable for different water area environments.

The invention provides a self-supervised multi-task underwater image restoration method based on an underwater imaging model, and the method comprises the following steps: carrying out the color cast correction of an underwater image collected by an underwater robot through an adaptive color balance algorithm, and obtaining an image after the color cast correction; obtaining the transmissivity of the image after the color cast correction through a transmissivity estimation network; enabling the image after color cast correction to pass through a background light estimation network to obtain background light; enabling the image after color cast correction to pass through a clear image reconstruction network to obtain a reconstructed clear image; and the background light and the transmissivity of the reconstructed clear image are synthesized through a Jaffe-McGammery underwater imaging model, and training is carried out in a self-supervision mode to obtain a final enhanced image. According to the method, an end-to-end self-supervised learning architecture is adopted, network training can be completed without large-scale annotation of a data set, the method has the advantages of low training cost and high generalization ability, and efficient image restoration can be realized in a complex and changeable underwater environment.

The invention belongs to the technical field of fluorescence spectrum collection, and particularly relates to a quasi-three-dimensional fluorescence spectrum collection method and spectrograph based on a software phase locking technology, and the method comprises the following steps: respectively modulating coprime modulation frequencies of a plurality of laser light sources with different wavelengths, and synchronously exciting the laser light sources to the surface of a sample; a fluorescence signal generated on the surface of the sample is received and processed by a linear array CCD detector to obtain a multi-wavelength spectral signal simultaneously containing background light, scattered light and fluorescence components; inputting the multi-wavelength spectral signal into a software phase-locked amplification system, introducing a Costas ring to the software phase-locked amplification system for real-time tracking and correction, and generating a synchronous reference signal consistent with the laser modulation frequency; inputting the synchronous reference signal into a software lock-in amplifier, and extracting a plurality of pure fluorescence spectrum components excited by specific-frequency laser; and synthesizing the plurality of pure fluorescence spectrum components to finally form a quasi-three-dimensional fluorescence spectrum.

An active infrared system may include at least one metamaterial optical element. The active infrared system may also include at least one lens assembly optically aligned with the at least one metamaterial optical element. The active infrared system may also include at least one active camera optically aligned with the at least one metamaterial optical element. The at least one metamaterial optical element of the active infrared system may also be configured with at least a reflection mode for reflecting at least one light waveband reflected by a remote object and a transmission mode for transmitting a uniform background light that is wider than the at least one light waveband reflected by the remote object.

The invention provides a laser glass defect real-time detection method which comprises the following steps: collecting fluctuation data of ambient light intensity and vibration frequency, capturing initial image data of a laser glass crack area, positioning a crack intersection point, analyzing a gray value attenuation distribution mode of the crack intersection point, and obtaining a quantitative index of spectral interference; obtaining a shadow micro-tremor inhibition effect of branch textures, and quantitatively evaluating the residual covering degree of background light artifacts on a crack edge structure in combination with an optimized crack intersection gray level uniformity index; and executing the determined pulse frequency configuration scheme, obtaining a laser glass defect detection image sequence in real time, evaluating the improvement degree of the real-time detection image sequence relative to initial image data, quantifying the multi-dimensional imaging optimization effect of the mesh crack texture, and dynamically generating a light source parameter adjustment sequence.

A method and system are provided for rapidly determining equi-depth histogram (ED histogram) boundaries for single photon arrival times without storing complete photon timestamp histories. A plurality of control values (CVs) is initialized for a plurality of binners that classify photon events as early or late relative to the respective CVs. Upon detecting photon arrivals, early and late arrival counts are used to update the CVs using an improved stepping strategy. The disclosed stepping strategy includes scaling a base step size, smoothing with exponential smoothing, temporally decaying the smoothed step size, and further smoothing to produce the step size for updating the CV. The disclosed stepping approach enables the CVs to rapidly converge to the desired quantile locations with low bias and variance compared to previous methods. The optimized stepping strategy is robust to noise and background light, providing accurate distance estimates while reducing bandwidth requirements.

The invention discloses a multi-wavelength dynamic interferometer measurement error correction method, and relates to the technical field of interference measurement, and the method comprises the steps: collecting a multi-wavelength interferogram; based on ideal interference light intensity distribution, background light intensity fitting, removal, light intensity adjustment distribution fitting and amplitude normalization are completed through polynomial fitting, and the problem of uneven light intensity distribution is corrected; carrying out Lissajous figure phase correction; adopting an AIA iterative algorithm to extract a single-wavelength phase, and then calculating phase information corresponding to a synthetic wavelength through a multi-wavelength synthesis algorithm; and carrying out dimension reduction on the surface shape data by adopting a PCA method, calculating a mahalanobis distance and removing abnormal signals, and averaging the original surface shape of the reserved data to obtain a final surface shape. According to the method, a polynomial fitting and Lissajous figure fitting double correction technology and a principal component analysis and mahalanobis distance anomaly elimination technology are combined as the core, the problems of phase shift errors, uneven light intensity, multi-wavelength synthesis error amplification and the like are solved in a targeted mode, and full-automatic high-precision measurement error correction is achieved.

The application provides a SiPM front-end circuit with background light suppression, wherein the cathode of the external APD is connected with an external high-voltage power supply; the input end of a background light intensity sensing and concurrency detection threshold generation circuit is connected with the anode of the external APD, and the output end is connected with the input end of a concurrency detection circuit; the input end of an OR tree is connected with the output end of a SiPM pixel, and the output end is connected with the input end of the concurrency detection circuit; the external APD is used for sensing the background light intensity; the background light intensity sensing and concurrency detection threshold generation circuit is used for outputting a binary threshold according to the background light intensity; the SiPM pixel is used for outputting a response voltage according to a return signal; the OR tree is used for outputting a pulse sequence according to the response voltage; and the concurrency detection circuit is used for outputting a signal capable of reflecting the time information of a target return signal according to the pulse sequence and the binary threshold, so that the background light can be effectively suppressed, and the performance index of a laser radar receiver is improved.

The invention relates to a method and a device for detecting dirt on a window of a laser radar, wherein - a laser beam is emitted by an emitter of the laser radar into a detection area, and - light present in the detection area is detected by a receiver of the laser radar, characterized in that - an intensity image of a gray-scale image as a laser reflection intensity is generated from the light reflected and detected as a result of the emission of the laser beam, - a background light image of a gray-scale image as background light is generated from the light detected without emission of the laser beam, - common features of the intensity image and the background light image are analyzed, and - a conclusion is drawn that dirt is present on the window when a preset number of common features is below.

To remove a non-resonance background signal without replacing a sample.SOLUTION: The nonlinear optical device 102 includes an irradiation part 106 for generating pump light, Stokes light, first probe light, and second probe light delayed from the first probe light and irradiating a sample with them, and a detector 108 for detecting the intensity of scattered light from the sample. When the sample is irradiated with the pump light and the Stokes light, resonance and a non-resonant background are generated, and when the sample is irradiated with the first probe light, an intensity of a rising portion of a non-resonant background (NRB) signal is detected without detecting an intensity of a resonance signal, and when the sample is irradiated with the second probe light, an intensity of a signal in which a falling portion of the NRB signal and the resonance signal are mixed is detected. The optical path lengths of the first probe light and the second probe light are set so that the intensity of the rising portion and the intensity of the falling portion of the NRB signal are equal to each other.SELECTED DRAWING: Figure 1

The application provides a deep-sea underwater sequence image enhancement method and device, electronic equipment and storage medium. Strong prior information is extracted from an obtained original deep-sea underwater sequence image and target object segmentation is performed, and a degraded region is detected based on a segmented target object region. A global background light is estimated from an edge region of the degraded region through a physical model, the estimation accuracy of transmittance is improved by using a color line prior theory, the degraded region is repaired according to the optimized transmittance, and a restored deep-sea underwater sequence image is obtained. The restored deep-sea underwater sequence image is enhanced by combining a FUnIE-GAN network and a suirSIR network. Color transfer is performed according to underwater sequence image content similarity, and sequence image color consistency is ensured. The application realizes color, illumination and definition enhancement of the deep-sea underwater sequence image, maintains sequence image color consistency, and ensures time smoothness of the output sequence.

This invention discloses an underwater image enhancement method and apparatus based on color perception fusion attention and background light removal contrast learning. The method includes: extracting color information from the original underwater image using a designed color extraction module; inputting the color information into a local color recovery branch to obtain reasonably distributed color weight information; passing the original underwater image through a triple attention branch to restore details and blur information in the image, obtaining an underwater enhanced image rich in detail and texture information; inputting the reasonably distributed color weight information and the underwater enhanced image rich in detail and texture information into a global light recovery branch, and using a contrast learning strategy to adjust the global light characteristics of the underwater image, finally obtaining the restored underwater image enhancement result. This invention can effectively improve the enhancement performance in underwater scenes, while eliminating the degradation effect of complex underwater environments on images, and realistically restoring the color and texture details of the image.

The application provides an optical imaging lens and an optical imaging device for collecting a welding image. The optical imaging lens comprises, in sequence from an object side to an image side, an object side lens group, a filter and an image side lens group. The object side lens group comprises, in sequence from the object side to the image side, a first lens, a second lens and a third lens. The second lens and the third lens are cemented to form a first cemented lens. The first lens has positive refractive power, and the first cemented lens has negative refractive power. The filter is a high-pass spatial filter for filtering out a low-frequency region corresponding to welding background light, and the high-pass spatial filter is located on a stop surface of the optical imaging lens. The image side lens group comprises, in sequence from the object side to the image side, a fourth lens, a fifth lens and a sixth lens. The fourth lens and the fifth lens are cemented to form a second cemented lens. The second cemented lens has negative refractive power, and the sixth lens has positive refractive power. The optical imaging lens can effectively suppress strong background light interference and has a compact structure.