236 results about "Dynamic imaging" patented technology

The invention relates to the technical field of magnetic resonance imaging, in particular to an intelligent sparse low-rank non-Cartesian magnetic resonance dynamic imaging method, which comprises the following steps of: acquiring magnetic resonance k-space data which is subjected to non-Cartesian continuous sampling by adopting multiple coils, continuously sampling data, rearranging the continuously sampled data along a time dimension by using a framing operator to obtain under-sampled k-space data, and then inputting the framed non-Cartesian under-sampled k-space data to be reconstructed into a trained network for image reconstruction. And reconstructing a final dynamic image through depth space-time sparsity, time low-rank learning, data consistency verification and loss function constraint. Compared with the prior art, the non-Cartesian magnetic resonance dynamic image reconstruction method has the advantages that the image is reconstructed through multiple times of network feedback iteration, the reconstruction speed of the non-Cartesian magnetic resonance dynamic image is greatly increased, and the temporal-spatial resolution is improved.

The invention discloses an HDR image reconstruction method based on progressive feature alignment and quality guide fusion, and the method comprises the steps: inputting a to-be-processed LDR image sequence into a trained progressive quality guide image reconstruction model, and obtaining an image reconstruction result; according to the model, after an input LDR image sequence is linearized, a progressive variable feature alignment module aligns non-reference frame features through a multi-scale pyramid and cascade deformable convolution, and multi-scale features are output through exposure perception modulation; the quality guide motion compensation module iteratively optimizes an optical flow field and a confidence coefficient mask through a cascade optical flow quality refining structure block; and the structure maintenance fusion module aligns the HDR sequence by using the optical flow field, performs dynamic weighted fusion in combination with a confidence mask, and finally enhances details through a Laplace attention mechanism and outputs a ghosting-free HDR image. According to the method, through progressive alignment and fusion of quality perception, the balance problem of ghosting and detail loss in dynamic HDR imaging is solved.

The invention discloses a tympanic membrane repair postoperative wound assessment method based on artificial intelligence, and relates to the technical field of medical assessment, and the method comprises the steps: obtaining multi-modal image data of a reference tympanic membrane and a target tympanic membrane through a multi-modal dynamic imaging fusion technology, determining a target biomechanical feature ratio through a biomechanical feature fusion technology, and obtaining a target tympanic membrane target biomechanical feature ratio; the method further comprises the steps of obtaining a physiological parameter set of the reference tympanic membrane and the target tympanic membrane, training an associated parameter prediction model to construct a metabolism-mechanical associated model, and achieving accurate evaluation of tympanic membrane wound healing conditions. The invention also covers related electronic equipment, a computer readable storage medium and a computer program product.

The invention provides a dynamic recognition system and method based on a light-operated nerve synapse array, and relates to the technical field of photoelectric pulses, and the system comprises a lens imaging module which is configured to collect light signals and transmit the light signals to the light-operated nerve synapse array so as to adjust the resistance value of the light-operated nerve synapse array; the displacement buffer module is configured to receive the serial input signal of the micro-control unit, convert the serial input signal into a parallel output signal, and transmit the parallel output signal to the light-operated nerve synapse array after the register is filled up; the light-operated nerve synapse array comprises a plurality of light-operated nerve synapses, and under the condition that the parallel output signal is low level, the corresponding target light-operated nerve synapses work and are connected with the analog-to-digital converter; the analog-to-digital converter is configured to collect a voltage value of the target light-operated nerve synapse and determine a resistance value of the target light-operated nerve synapse based on the voltage value; and the dynamic imaging module is configured to convert the resistance value into a gray value image.

The invention provides an exhaled gas alcohol content intelligent verification system based on image recognition, relates to the technical field of intelligent detection, and aims to solve the problems that a traditional sensor is prone to environmental interference, needs frequent calibration and is insufficient in dynamic response. Comprising a gas-sensitive developing unit, a multispectral dynamic imaging unit, a data processing unit and a closed-loop control unit, the gas-sensitive color development unit adopts a reversible gas-sensitive film and generates a color change signal through an alcohol specific color development reaction; the multispectral dynamic imaging unit is combined with an ambient light suppression and dynamic region positioning technology to capture spectral reflectivity time sequence data in a color development process; the data processing unit maps the chromaticity characteristic into an alcohol concentration value based on a Gaussian process regression model, and triggers near-infrared auxiliary verification through confidence evaluation; and the closed-loop control unit maintains a constant detection environment through the temperature control and airflow stabilization module. According to the scheme, non-intrusive high-precision detection of the alcohol concentration in a complex environment can be realized.

The invention discloses a thoracic cavity heart sound signal non-contact extraction system and method based on structured light. The system comprises a structured light projection module, an image acquisition module, an image processing and displacement extraction module and a signal processing and trigger point identification module, structured light is projected on the surface of the chest of a human body to form a regular pattern, and a high-speed image acquisition means is utilized to record micro displacement change generated by light spots under cardiac drive. Thoracic cavity vibration information is extracted through an image processing technology, periodic feature points corresponding to a cardiac rhythm are recognized in combination with a time sequence analysis strategy, a thoracic cavity heart sound signal is extracted, rhythm analysis is conducted, and a cardiac trigger point is output to serve as a trigger signal for synchronous control of medical equipment. The technical problems of signal distortion, equipment interference, potential safety hazards, inconvenience in use and the like in a strong electromagnetic environment in a traditional contact mode are solved, and a high-precision synchronous trigger signal is provided for dynamic imaging.

The invention relates to the technical field of material performance testing, in particular to a neat paste flow testing method and system based on multi-mode dynamic imaging. The test method comprises the following steps: collecting a continuous infrared image sequence of a neat paste free flowing process; synchronously triggering visible light supplement in a flowing initial stage, and obtaining at least one frame of visible light image; performing registration fusion on the visible light image and the infrared image at the corresponding moment to generate an enhanced image frame; extracting a neat paste contour in real time based on the enhanced image frame, and calculating dynamic parameters; according to the change trend of the dynamic parameters, the flowing stability opportunity is adaptively judged; and triggering final contour extraction at a stable opportunity, and calculating static morphological parameters and dynamic process parameters. Through the multi-modal dynamic imaging and intelligent image fusion technology, complex edge contours are accurately extracted, impurity interference is eliminated, and the measurement precision is improved.

The invention discloses an automatic instrument reading method and system based on embedded machine vision. The method comprises the following steps: deploying an embedded image acquisition unit with wide dynamic imaging capability; performing multi-mode preprocessing of white balance correction, contrast enhancement and noise suppression on the image; self-adaptively identifying the instrument type and positioning a key area by using a lightweight convolutional neural network; hough transform and sub-pixel edge detection are adopted for a pointer type instrument to achieve high-precision angle analysis, and optical character recognition is completed for a digital instrument through a bidirectional long-short-term memory network; and finally, fusing multi-frame results through Kalman filtering, evaluating credibility, and outputting stable readings with timestamps. According to the technical scheme, high-robustness, high-precision and low-delay automatic reading can be realized at the embedded end, and the operation stability and the long-term adaptability of the system in a weak network environment are remarkably improved.

The invention discloses a variable view field Linnik interference microscopic system and a measurement method thereof, and belongs to the field of laser measurement instruments, and a variable diaphragm is introduced into a reference arm of an interference system to realize matching of objective lenses of different test arms, so that light field spatial correlation under speckle illumination is maintained; meanwhile, a light source system with a delay line structure is adopted to accurately compensate the optical path difference introduced by the asymmetric objective lens configuration, so that the acquisition of a high-contrast interference pattern is realized. The method can effectively improve the quality of an interference image, has a depth selection function, and is suitable for dynamic phase imaging in different view field ranges. The technical scheme of the invention shows good imaging effect and adaptability in the aspects of dynamic imaging and depth layering.

The invention discloses an artificial intelligence traffic abnormal event identification method based on a high-altitude visual angle of an unmanned aerial vehicle, particularly relates to the field of traffic management, solves the problem of abnormal event identification caused by parallax distortion in a high-speed cruise scene, and optimizes parallax distortion through cooperation of flight control and zooming driven by a continuous frame motion intensity baseline. Stabilizing a target contour by using a dynamic imaging window, constructing a sparse confidence kernel to analyze multi-dimensional motion, adaptively filtering low-quality candidates and finely trimming abnormal coordinates; the flight attitude and view finding parameters are dynamically adjusted according to the weight of the abnormally dense area, and high-altitude wide-angle coverage and single-vehicle fine-grained monitoring coexist; carrying out confidence analysis to remove parallax artifacts, generating coordinates after abnormal candidate rechecking, and driving flight control fine tuning; each processing link compresses the sensing bandwidth cooperatively, the alarm confidence is improved, the decision chain time delay of discovery, positioning and following is shortened, the coordinate precision and the pushing time efficiency under the conditions of complex illumination and severe parallax are ensured, and the reliable intelligent sensing capability is provided for traffic management.

A system for increasing a frame rate of a dynamic image includes an input for receiving a set of consecutive image frames of a first dynamic image having a first plurality of image frames and a first frame rate. The system further includes a deformation encoding neural network coupled to the input and configured to derive at least one parameter characterizing dynamics of the set of consecutive image frames and to generate an interpolated image frame based on the at least one parameter, and a post-processing module coupled to the deformation encoding neural network and configured to receive one or more interpolated image frames from the deformation encoding neural network, to create a second plurality of image frames comprising the one or more interpolated image frames and the first plurality of image frames, and to generate a second dynamic image using the second plurality of image frames, the second dynamic image having a second frame rate higher than the first frame rate.

A Multi-Angle Dynamic Image system provides multi-angle observation capabilities comprising lamps strategically positioned to obtain high quality images of the security documents or items under analysis, to obtain images with variations in the observation angle of the security document or item under study. The system includes a box platform for placing the security document or item thereupon, the box platform changes its orientation, allowing the system to capture the variations in color and structure as the orientation and the angles of the observation and illumination change. The system also includes a high-resolution linear camera to capture the intricate details while avoiding distortion and parallax issues. The system also includes a computer configured to run algorithms to process image acquisition data for a complete set of observation angles, to pre-process image acquisition data including crop and image standardization, to calculate differences between adjacent angle images, eliminate noise, to calculate a total optical flow using the images at different angles and their differences to generate the Dynamic Images vectorial field, one per orientation, and the Dynamic Map, a heat map generated using the magnitude from the Dynamic Image vectorial field, and calculate from the Dynamic Image the different parameters associated with dynamic properties of the OVD.

The invention discloses a microfluidic-EICP combined dynamic visual monitoring system and method for a heavy metal polluted soil remediation process, and relates to the technical field of soil monitoring. The microfluidic-EICP combined heavy metal polluted soil remediation process dynamic visual monitoring system comprises a microfluidic reaction module, a multi-mode sensing module, a dynamic imaging module and a data analysis module, and the microfluidic reaction module comprises a heavy metal pollution simulation unit and an in-situ reaction control unit. The multi-mode sensing module comprises a substrate layer, a chemical sensing layer and a data interface layer, the dynamic imaging module comprises an optical imaging unit and a spectral analysis unit, and the data analysis module is electrically connected with the communication module. According to the technical scheme provided by the invention, multi-physical field cooperative monitoring of a chemical field, a mechanical field and a permeation field in the prior art is realized, and the cross-scale correlation analysis capability of a micro crystal growth mechanism and a macroscopic soil body modification effect is improved.

The invention discloses a self-adaptive high-dynamic-range image generation method in a chemical monitoring scene, and belongs to the technical field of high-dynamic imaging and computational imaging. Performing registration preprocessing on the acquired reference image based on a brightness consistency criterion; constructing a high dynamic range image generation network model, inputting the reference image into the model, performing feature extraction and fusion through a multi-scale network, and generating a high dynamic range image based on the fused features; performing tone mapping on the generated high dynamic range image based on a brightness consistency criterion; and comparing the generated high dynamic range image with a reference image, calculating a pixel-level loss function and multi-dimensional perception loss, and optimizing an image generation process through a back propagation training network model. According to the method, imaging details of different scales are captured through a multi-scale feature processing method, so that the generated image is better in brightness range and details, and the expressive force of the image under a complex illumination condition is ensured.

The invention belongs to the technical field of nuclear equipment monitoring, and aims to solve the problems of spatial resolution reduction caused by a multi-source acoustic signal aliasing effect in a complex industrial environment and feature extraction difficulty caused by industrial noise and fault sound source spectrum overlapping. According to the method, spatial decoupling is carried out, sparse Bayesian learning and minimum variance undistorted response beam forming joint optimization is carried out, a sound source orientation is preliminarily estimated, synchronous extrusion wavelet transform and NMF joint time-frequency analysis is carried out, and a spatial anomaly acoustic diagnosis result is obtained. Sound source transient characteristics and energy evolution laws are extracted through time-frequency conjoint analysis, a multi-dimensional characteristic space is constructed, the number of fault types is determined for fault type classification, and three-dimensional coordinate mapping and error feedback are displayed; the system comprises an airspace decoupling module, a time-frequency decomposition module, a feature fusion module and a dynamic imaging module. According to the invention, the sound source positioning precision can be realized, and the resolution limitation of traditional beam forming is broken through.

The invention relates to the technical field of deep learning, and provides a mammary gland blood oxygen dynamic imaging method and system based on multispectral fusion, and the method comprises the steps: irradiating mammary gland tissues, and collecting mammary gland tissue reflected light image sequences under different wavelengths to obtain multispectral time sequence data; constructing an adaptive weight prediction network model, and dynamically predicting the fusion weight of each spectral wavelength at different moments in the future according to the blood oxygen change intensity and historical time sequence information at the current moment; performing multi-resolution time sequence modeling on the multi-spectral time sequence data, respectively extracting short-term, medium-term and long-term time sequence features, and performing weighted fusion on the features of different spectral wavelengths through a fusion weight to obtain fusion feature data; and performing inversion processing on the fused feature data, and calculating oxyhemoglobin saturation distribution of a continuous time sequence in real time to obtain a dynamic blood oxygen image sequence. According to the invention, the blood oxygen detection precision and the depth resolution are improved, and high-precision dynamic imaging of the blood oxygen saturation of the breast tissue is realized.

The invention discloses a dynamic image motion correction method based on a graph neural network, and the method comprises the following steps: a), constructing a target region trajectory tracking model based on the graph neural network, and achieving the high-precision motion trajectory modeling; b) analyzing an image displacement mode in real time through a dynamic discrimination algorithm; and c) realizing adaptive image motion correction based on the target area track features. According to the method, the problem of complex motion trail modeling limitation caused by dependence on fixed template matching in a traditional method is innovatively solved, and the problem of spatial-temporal characteristic aliasing caused by unsteady state deformation of nervous tissues is effectively solved. According to the technical scheme, the dependence on a hardware synchronization signal acquisition module is eliminated, the resource configuration requirement of the edge computing equipment is remarkably reduced, and meanwhile, the multi-scale time sequence integration efficiency is improved. According to the method, dynamic imaging reconstruction of subcellular neural activities can be realized, and dynamic change details in a target neuron issuing process can be accurately restored.

The invention relates to an impregnation machine resin liquid level intelligent sensing and early warning method. The method comprises the steps that multiple sampling positions are arranged in a resin liquid level area in impregnation machine equipment; performing noise suppression and signal normalization processing on the time domain dielectric signal data set; performing feature classification on the data samples under different working conditions; adopting the historical liquid level response database to construct a multi-working-condition adaptive baseline model; a standardized time domain dielectric signal sequence obtained through actual sampling is input into the multi-working-condition self-adaptive baseline model, and a liquid level local abnormal trend signal is obtained; performing multi-window space-time distribution dynamic imaging processing on the liquid level local abnormal trend signal; inputting the amplitude, continuity and spatial diffusion characteristic parameters of the trend change into a historical false alarm and artifact event characteristic library; and dynamically generating a self-adaptive early warning threshold value for the liquid level abnormal trend signal after the artifacts are removed. According to the invention, high-sensitivity acquisition and dynamic amplification of local electromagnetic response caused by small fluctuation of the resin liquid level can be realized.

The invention belongs to the technical field of biochemistry, and relates to a fluorescence / photoacoustic bimodal probe responding to Cu (I) and a preparation method and application thereof. The fluorescence / photoacoustic bimodal probe responding to Cu (I) has high selectivity and sensitivity, has efficient tumor targeting ability, can be used for dynamic tracing of Cu (I) in tumor, can dynamically image Cu (I) in tumor by combining with a three-dimensional photoacoustic / living body fluorescence imaging technology and the probe HCyCu1, provides a new detection means for detection of Cu (I), and has wide application prospects. And a potential tool is provided for tumor diagnosis. According to the preparation method of the bimodal probe, the adopted raw materials are easy to obtain, the reaction conditions are mild and easy to control, the reaction cost is saved, and the yield of a target product is guaranteed. The structural formula of the probe is as follows: # imgabs0 #.

The embodiment of the invention relates to the technical field of terminals, in particular to a method for generating an HDR image and electronic equipment, and can improve the display effect of the HDR image. The method comprises the following steps: acquiring a first HDR image, and performing tone mapping on the first HDR image to obtain a second HDR image; the first HDR image comprises a first highlight area, and the first highlight area comprises a highlight object; the second HDR image comprises a second highlight area, and the second highlight area corresponds to the first highlight area; correcting the gradient direction of the first pixel in the second highlight area into the gradient direction of the second pixel in the first highlight area to obtain a third HDR image; the second pixel corresponds to the first pixel; wherein the gradient direction of one pixel is positive and negative of the difference value between the brightness value of the next pixel of the pixel on a first direction axis and the brightness value of the pixel, and the first direction axis comprises an x axis and a y axis; wherein the dynamic imaging range of the third HDR image is smaller than that of the first HDR image, and the third HDR image is used for displaying.

The invention discloses a thoracic cavity three-dimensional electrical impedance tomography method and thoracic cavity three-dimensional electrical impedance tomography equipment. The method comprises the following steps: acquiring a three-dimensional point cloud of the appearance of a chest area of a testee to establish a three-dimensional chest model; carrying out equipment self-inspection and checking the bonding condition of the electrode; generating a determined excitation signal and injecting the excitation signal into the testee; acquiring a voltage signal of each electrode; separating EIT and ECG signals and filtering the EIT and ECG signals; according to a three-dimensional thoracic cavity model of the testee, performing positive problem calculation on the voltage signal to obtain the potential of each electrode of the three-dimensional thoracic cavity model; and performing three-dimensional reconstruction by adopting a single-step Gaussian Newton method to obtain a lung ventilation change electrical impedance imaging graph. According to the method, the three-dimensional thoracic cavity model of the testee is constructed, the positive problem solution is performed on the voltage signal, and the image reconstruction is further performed, so that the real-time high-precision three-dimensional dynamic imaging of the thoracic cavity of the testee can be completed, and the imaging accuracy is high.

The invention discloses an X-ray tomography in-situ testing device and method suitable for a seawater high-pressure environment. The X-ray tomography in-situ testing device comprises an X-ray source, a collimator, a flat panel detector, a seawater pressure cabin and a seawater pressure control device. During detection, the X-ray source is started, the sample is started to move spirally, the flat panel detector collects projection data, then a cross-sectional image is reconstructed through an existing method, and the X-ray tomography in-situ test of the sample in the seawater high-pressure environment is achieved. In order to solve the problems that a seawater in-situ detection device in the prior art is insufficient in penetrating power, low in resolution ratio, limited in sample movement freedom degree and poor in high-pressure environment adaptability, the invention discloses an X-ray tomography device and method, and in-situ dynamic imaging can be carried out on a large component in a seawater high-pressure environment. In-situ observation of micron-sized damage and defects (100-200 microns) is realized, and meanwhile, an imaging view field is expanded through a multi-degree-of-freedom sample table and a spiral scanning method, so that the detection efficiency is improved.

The invention discloses an airborne dynamic imaging-oriented image quality enhancement calculation processing system and a method thereof, and relates to the technical field of calculation optics. The system comprises an illumination module, a collimation module, a confocal module, a beam splitting module, an angle selection filtering module and an imaging module. The angle selection filtering module changes the incident angle of a light beam through physical movement or rotation, so that the angle selection filtering module excites a Berman mode in a near-zero dielectric constant double-layer film, and real-time switching between normal incidence low-pass denoising and oblique incidence high-pass sharpening is achieved. According to the invention, switching of two typical image processing functions can be realized only through incident angle adjustment without introducing an electrical regulation and control element, so that sharpening and denoising function integration is realized in a single optical structure, and the system has millisecond-level angle switching, low power consumption and a compact linear folded optical path, and is suitable for airborne high-speed imaging.

The invention discloses a pure organic scintillator material and a preparation method and application thereof, and belongs to the technical field of organic photoelectric functional materials, and the pure organic scintillator material provided by the invention is obtained by taking diphenyl phosphorus chloride as a raw material through two-step reaction and crystal culture. The preparation method has the advantages of mild reaction conditions, simple synthesis, cheap raw materials, easy product purification and the like, and provides a new idea for preparing the organic scintillator. A pure organic scintillator material is ground and then doped with polyvinyl alcohol to prepare the scintillation screen, and the prepared scintillation screen has the advantages of radiative brightness, high imaging resolution, low detection limit, bendability, crimpability and the like, and successfully realizes static, curved, three-dimensional and dynamic X-ray imaging.

To enhance reliability of breath-holding failure determination.SOLUTION: A kymographic apparatus comprises: a waveform acquisition part that acquires a lung field signal waveform regarding a lung field and a periodic signal waveform synchronous with a heartbeat from a dynamic image acquired in radiation kymography based on photographing conditions including breath-holding instructions; and a determination part that determines the occurrence of a breath-holding failure during the radiation kymography, on the basis of the result of comparison between the acquired lung field signal waveform and the acquired periodic signal waveform.SELECTED DRAWING: Figure 5

The invention relates to the technical field of photoelectric detection, in particular to a photocurrent imaging system based on a probe station and an electrometer. The system generates a focused detection light beam through a light path system, the focused detection light beam irradiates a sample carried by a probe station after being spatially modulated by a mask plate, weak light current signals generated by the sample are collected by an electrometer, and a high-resolution light current distribution image is generated by combining scanning motion of a high-precision electric control displacement platform and intelligent processing of computer software. A physically-driven signal enhancement model, a multi-dimensional noise suppression algorithm and a dynamic imaging optimization formula are innovatively designed, the problems that in the prior art, weak light current detection precision is low, the scale connection error is large, and imaging efficiency is insufficient are solved, accurate quantitative analysis of the photoelectric characteristics of materials is achieved, and the method is suitable for popularization and application. The method is suitable for semiconductor device research and development, solar cell performance evaluation, biosensor detection and other scenes, and has both detection precision and application flexibility.

The invention discloses a three-spot welding dynamic imaging stabilization detection method based on motion compensation modeling, and relates to the technical field of photovoltaic energy monitoring, and the method comprises the following steps: obtaining an acoustic vibration signal, a picture time marking signal and a jig lifting displacement signal of the whole jacking process of a compressor shell, carrying out the time synchronization and feature fusion of the obtained signals, and carrying out the feature fusion of the obtained signals; and generating a resonance distribution band for constructing a dynamic reference model for subsequent time sequence analysis. According to the invention, through multi-source signal synchronous modeling and light machine closed-loop regulation and control, millisecond-level consistency of a jacking action and an imaging process is realized. Exposure and vibration phases are accurately controlled through staggered anchor points, a drift sketch, a baseline ring and an alignment key, pixel drift and brightness fluctuation are remarkably reduced, the detection false alarm rate and the detection omission rate are reduced by 73% and 67% respectively, and high precision and high stability of three-spot welding dynamic detection are achieved.

The invention relates to the technical field of medical image analysis, in particular to a dynamic DR digestive tract radiography automatic tracking and focus marking system which comprises a dynamic DR imaging module, an image real-time processing module, a contrast agent motion tracking module and a focus intelligent marking module. A deep learning algorithm is utilized to segment a contrast agent flowing area in real time and construct a dynamic three-dimensional model of a digestive tract, a contrast agent movement track is analyzed and tracked in combination with time-space domain features, and meanwhile, based on morphological anomaly detection and comparison with a focus feature library, focus positions such as stenosis, ulcers and space-occupying lesions are automatically marked; the problems of image blurring and tracking offset caused by alimentary canal peristalsis are solved by adopting a self-adaptive registration optimization algorithm of dynamic DR images and motion characteristics of alimentary canal contrast agents; by means of the method, the problems that traditional digestive tract radiography depends on manual interpretation of dynamic DR images, the focus tracking efficiency is low, and marking is prone to omission are solved.

A sorting machine with a dynamic vision system is developed to provide dynamic lighting, imaging, and analysis of industrial materials while moving the conveyor. The sorting machine comprises a washing box, a vision system, a control unit, and a transferring unit. The vision system comprises dynamic imaging unit and dynamic lighting unit. The vision system is configured to provide a dynamic lighting and a dynamic imaging of industrial materials. The imaging unit comprises a camera, a camera movement unit, and a dynamic camera stand. The lighting unit comprises an optical section, a linear motion adjuster section, and a light angle adjuster section.