233 results about "Background light" patented technology

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 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.

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 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.

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 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 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 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.

The application discloses a kind of magnetically responsive hydrogel optical fiber and its preparation and application, belong to medical biomaterial field.The optical fiber includes from inside to outside: polyethylene glycol diacrylate and acrylamide photocrosslinking light transmission core layer;Calcium alginate low refractive index skin layer;Doped nano-magnetic response layer of ferriferrous oxide;And polydopamine grafting polyvinylpyrrolidone lubricating layer.It is prepared by coaxial extrusion and light / calcium step-by-step crosslinking.The structure realizes the spatial isolation and anti-interference of light transmission and magnetic drive, has low background light loss and anti-bending stability, has biomechanics matching, ultra-low friction and magnetic field accurate active navigation ability, solves the pain point that extremely soft optical fiber is difficult to directional intervention.Suitable for deep tissue precise photothermal therapy, in vivo continuous optical sensing and minimally invasive diagnosis and treatment integration and other frontier medical fields.

The invention relates to the technical field of laser radars, in particular to a vortex light laser radar which comprises a laser emitting unit, an optical receiving unit, an optical modulation unit, a signal detection unit, a signal acquisition and processing unit and a system structure unit. The optical receiving and modulating module divides echo light into a vortex channel and a reference channel through polarization beam splitting. The vortex channel performs orbital angular momentum modulation on echo light by using the receiving modulation unit, converts coherent signal light into annularly distributed vortex light, and filters incoherent noise light through the OAM spatial filtering assembly, thereby realizing spatial separation of signals and noise. The problem of interference of multiple scattered light and background light in a strong scattering medium is effectively solved, the detection signal-to-noise ratio, the maximum detection distance and the target resolution of the laser radar are remarkably improved, and the system is compact in structure, high in engineering practicability and particularly suitable for target detection in underwater, haze and other complex environments.

The application discloses a kind of garden plant health condition detection and early warning system based on spectral analysis, including adjustable frequency excitation light source, fluorescence detector, quadrature phase-locked demodulation module, phase frequency characteristic analysis module, early warning control unit and early warning output terminal, adjustable frequency excitation light source emits broadband sweep frequency modulation perturbation excitation light, quadrature phase-locked demodulation module executes operation filtering natural background stray light to the electric signal collected, phase frequency characteristic analysis module extracts characteristic relaxation frequency parameter when absolute phase delay parameter reaches forty-five degrees phase angle, early warning control unit sends instruction lock frequency and applies saturated light flash pulse, system calculates dynamic apparent electron transfer rate parameter, and according to temperature drift compensation baseline, executes double tolerance threshold comparison determination plant physiological stress state.The application avoids the defect of detection frequency band misplacement, eliminates the interference of strong background light and air temperature fluctuation, realizes the multi-dimensional joint early warning of early physiological stress.

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

This invention relates to a circuit and method for suppressing drift error and background light in a SPAD lidar. The SPAD array and readout circuit unit acquire optical signals; a target recognition algorithm unit measures the distance to targets within the effective field of view based on the optical signals to obtain distance measurement information; a laser power adjustment drive unit dynamically adjusts the output power of the laser emitting unit based on the distance measurement information; a nonlinearly modulated gated high-voltage drive circuit unit adjusts the drive voltage of the SPAD array and readout circuit unit based on the distance measurement information; and the laser emitting unit, acting as a pulsed laser source, emits laser light from its output end to an optical lens, which then illuminates the surface of the target within the effective field of view. This invention effectively suppresses SPAD drift error and improves the dynamic range, measurement accuracy, and background light suppression capability of the SPAD lidar.

This invention discloses an underwater image enhancement method based on a diffusion model with red-dark channel prior constraints. The method includes inputting a single-frame underwater raw image into the model and passing it through a joint estimation module of red-dark channel prior and quadtree, outputting transmittance and background light. These are then encoded by a physical condition encoder to generate a physical condition vector containing spatial attenuation priors and global background light constraints. This vector is used by the diffusion network for encoding and utilizes transmittance distribution and global background light information. In the reverse denoising process, a physical consistency layer and the Jaffe-McGlamery equation are combined to construct a physical consistency residual. The residual gradient calculated based on the physical model is injected as a guiding term into the noise prediction process. The enhanced image is iteratively generated through a denoising diffusion implicit model sampling process. The enhanced image is then forward-degraded and re-rendered through a cyclic consistency reconstruction branch. The cyclic consistency loss is calculated and used for reverse optimization of network parameters. This invention can reduce the color shift problems caused by background light misjudgment and transmittance overestimation.

A movement amount estimation device includes an image acquiring unit and an estimation unit. The image acquiring unit is configured to acquire a reflected light image, a background light image, and a camera image. The reflected light image contains distance information obtained by emitting light and detecting the light reflected from an object by a light receiving element. The background light image contains luminance information obtained by detecting background light relative to the light reflected from the object by the light receiving element. The camera image is captured by a camera element that is different from the light receiving element. The estimation unit is configured to estimate a movement amount of an estimation target using information of a captured object commonly detected in the reflected light image, the background light image, and the camera image.

This application discloses a method and related apparatus for judging the quality of light spots under dynamic background light. The method includes: vectorizing good and bad light spot images acquired under different background lights to obtain good and bad light spot image matrices under different background lights; vectorizing multiple light spot images to be detected acquired under dynamic background light to obtain a light spot image matrix to be tested under dynamic background light; inputting the good and bad light spot image matrices under different background lights, the label matrices corresponding to the good and bad light spot image matrices, and the light spot image matrix to be tested under dynamic background light into a semi-supervised multi-view learning model for processing to obtain a predicted label matrix of the light spot image matrix to be tested under dynamic background light; judging the quality of each light spot image to be tested under dynamic background light by the values ​​in the predicted label matrix, thereby improving the technical problem that existing technologies are difficult to effectively detect the edge contour of light spots under the influence of dynamic background light, thus affecting the light spot quality judgment results.

This invention relates to a photoelectric conversion and beam combining device for multiple-channel reception of the same echo optical signal in lidar. The device includes: a sealed box, a single-photon detector, and multiple echo signal receiving lines. The multiple echo signal receiving lines receive the same echo optical signal, process the echo signal, and then transmit the processed optical signal to the single-photon detector. All echo signal lines are housed in the sealed box. Each echo signal receiving line includes: an echo signal fiber, a collimating and focusing lens group, and a narrowband filter. The echo signal fiber receives the echo optical signal. The collimating and focusing lens group includes a collimating lens and a focusing lens. The collimating lens shapes the optical signal into parallel light. The focusing lens focuses the parallel light. The narrowband filter filters out stray light and atmospheric background light from the optical signal. This invention simplifies the optical receiving system components of lidar, reduces system cost, and minimizes signal errors.

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

A light detection and ranging (lidar) device may be coupled to a vehicle and configured to scan a surrounding environment to determine ranges to one or more objects in the surrounding environment of the vehicle. The lidar device may generate data that can be used to form a range image, which includes or is based on range data determined for the one or more objects. The lidar device may also generate data that can be used to form a corresponding background image, which includes background light intensity data that the lidar device measures during the scan. The background image or background image data may be used to add range data to the range image, correct range data in the range image, and / or evaluate the quality of the range data in the range image. In this way, the background image or background image data can be used to generate an enhanced range image that includes range data that is more comprehensive and / or more reliable than the range data included in the original range image.

The invention belongs to the field of three-dimensional measurement in computer vision, and particularly discloses a high dynamic range three-dimensional measurement method based on background light partition correction. A supersaturated area and a non-supersaturated area are distinguished through a proper background light intensity threshold value; then, an envelope value of background light intensity is further extracted, and a shallow saturation region and a deep saturation region are distinguished by combining a proper envelope threshold value, so that the influence of a higher harmonic signal caused by a supersaturation effect on partitioning can be effectively inhibited, and the partitioning accuracy is improved; and finally, performing PHE correction on the phases in the regions with different saturation degrees, thereby effectively solving the correction problem of non-uniform phase error distribution, and improving the measurement precision of the surface with non-uniform reflectivity.

The application relates to a method, system, device and storage medium for image background light illumination homogenization, which comprises the following steps: step S1: inputting an original image, obtaining a rectangular mask, and performing rank filtering on the original image using the rectangular mask to obtain a first image; step S2: performing mean filtering on the first image to eliminate high-frequency gray values in the first image and obtain a second image; and step S3: subtracting the second image from the original image to obtain a final processing image, and scaling the gray value of the final processing image to a preset value. In the application, the original image is filtered using the rectangular mask, which can reduce the difference of the gray values at different positions of the original image; the second image is subtracted from the original image to obtain a third image, which is used to obtain the gray difference value of each pixel point of the second image and the original image, highlight the contour edges in the image, and greatly reduce the problem of uneven image brightness.

The invention relates to a single-cell microneedle tip position image recognition system and recognition method, and is used for recognizing the tip position of a microneedle, the single-cell microneedle tip position image recognition system comprises an illumination unit, an imaging unit and an adjusting assembly, and the illumination unit is used for emitting light; a microneedle is inserted between the imaging unit and the illumination unit, and the imaging unit is used for collecting an image of the tip position of the microneedle; the adjusting assembly is connected with the imaging unit and used for adjusting the position of the imaging unit so that the needle point position of the microneedle can be located in the center of an image formed by the imaging unit. In the single-cell microneedle tip position image recognition system and recognition method, the illumination unit emits light to serve as background light of the microneedle, and the adjusting assembly can control the relative position between the imaging unit and the microneedle so as to ensure the definition and precision of the collected microneedle image; in addition, the tip of the microneedle is not in contact with the imaging unit and the illumination unit, so that the occurrence of adverse conditions such as damage and pollution of the microneedle is avoided.

A system maintains stable image colors of a user, such as face tones, when the user is at a computer display device and the user's image is transmitted to other persons, such as in an online meeting. The system adjusts the user's image based on factors such as the light, color and brightness of the computer display device, foreground light and color, background light and color, and light incident on the user and background.

The application discloses a kind of multi-wavelength dynamic interferometer measurement error correction method, it is related to interference measurement technical field, including: multi-wavelength interference chart acquisition;Based on ideal distribution of interference light intensity, background light intensity fitting is completed by polynomial fitting, removes, light intensity scheduling distribution fitting and amplitude normalization, corrects light intensity distribution uneven problem;Lissajous figure phase correction;Single wavelength phase is extracted using AIA iterative algorithm, and then the corresponding phase information of the wavelength is calculated by multi-wavelength synthesis algorithm;Dimensionality reduction is carried out on the surface shape data using PCA method, the Mahalanobis distance is calculated and the abnormal signal is removed, the original surface shape of the remaining data is averaged to obtain the final surface shape.The application takes polynomial fitting and Lissajous figure fitting double correction technology as the core, and principal component analysis combined with Mahalanobis distance abnormal rejection technology, specifically solves phase shift error, light intensity uneven and multi-wavelength synthesis error amplification and other problems, realizes full-automatic high-precision measurement error correction.

Example embodiments relate to taking images at certain predetermined angles in order to have consistent exposure throughout the images. An example embodiment includes a method. The method includes determining, using a lidar device, light intensity information of a surrounding environment of the lidar device. The light intensity information includes a plurality of angles within a threshold range of light exposure. The method also includes determining rotation times associated with each of the angles within the threshold range of light exposure. Further, the method includes based on the rotation times associated with each of the angles within the threshold range of light exposure, determining a plurality of target image times. In addition, the method includes capturing, by a camera system, a plurality of images at the plurality of target image times.

The invention discloses a method, device and equipment for adjusting background light of a terminal with a screen and a storage medium, and relates to the technical field of intelligent hardware. The method comprises the following steps: acquiring figure video data, text data and audio data in a video; inputting the character video data, the text data and the audio data into a sentiment analysis model, extracting modal features and inter-modal features of the character video data, the text data and the audio data through the sentiment analysis model, and calculating decoupling feature input according to a relation among the modal features, the inter-modal features and the decoupling features; outputting a target sentiment score predicted value according to a mapping relationship between the decoupling features and the sentiment score predicted value; and adjusting the background light according to the target emotion score predicted value. According to the embodiment of the invention, the real-time adaptive adjustment of the background light is realized, and the background light interaction adjustment capability is improved.