191 results about "Spectral filtering" patented technology

The invention relates to the technical field of photovoltaic module detection, in particular to a TOPCon battery piece defect detection device and a TOPCon battery piece defect detection method. The optical imaging module comprises a 25,000,000-pixel camera, a three-color integral light source array and a multispectral optical filter group, and the light source array is composed of red, green and blue LEDs and supports pulse synchronous triggering; the traditional algorithm processing module is integrated with a Halcon image processing library and is configured with a VarThreshold operator dynamic threshold segmentation unit, an adjustable kernel size corrosion filtering unit and a light and shade separation unit, and an Erosion Rectangle1 operator is used for corrosion filtering; the AI defect detection module is internally provided with an improved YOLOv8 neural network model, and the model structure comprises a Backbone network embedded with a CBAM attention mechanism, a BiFPN network bidirectional feature pyramid and a dynamic loss function optimizer; according to the technical scheme, the limitation problems of low positioning precision, poor detection efficiency, single defect identification dimension and the like of an artificial vision or traditional probe contact detection means can be solved.

An optical comb generator receives light from at least two continuous wave laser sources, produces a different frequency comb from each laser source, and produces an output that it the simultaneous combination of the different frequency combs. The different frequency combs span different frequency bands, but at least partially overlap in frequency with an adjacent comb in a region of overlap. A spectral filter produces a filtered output that has at least one pair of tones from the region of overlap, the pair of tones comprising one tone from each of two adjacent combs. Feedback control based on the filtered output is applied to adjust the light entering the comb generator such that the frequencies and phases of the pair of tones from the region of overlap are aligned. In this way, the multiple different overlapping combs are stitched together to form a single seamless comb spanning a broader frequency range.

A multispectral image capture device includes an imaging platform having arranged thereon an image sensor comprising a photosensitive surface and an optical unit, a gimbals system for controlling a line of sight of the image sensor, a filter wheel comprising a series of n spectral filters arranged between the image sensor and an imaging target; and a drive system configured to rotate the filter wheel at a constant velocity so as to bring each of the spectral filters into a line of sight between the image sensor and the imaging target. A controller is adapted to synchronize movement of the imaging platform, control of line of sight of the image sensor with the gimbals, and constant rotation of the filter wheel, such that the image sensor captures a sequence of overlapping step-and-stare images through the series of rotating spectral filters without changing a speed of rotation of the filter wheel.

The invention relates to the technical field of image recognition, and particularly discloses an image recognition method for multispectral bird monitoring, which comprises the following steps of: S1, carrying out multi-angle shooting on a bird monitoring area by utilizing a multispectral camera equipped with a plurality of different spectral filters to obtain image data of a plurality of spectral bands; the collected image data is preprocessed; s2, performing feature extraction according to the spectral band type of the preprocessed image data; feature fusion is carried out; s3, constructing an integrated classifier; training an integrated classifier by using the fused image data set, and optimizing classifier parameters; and S4, acquiring a multispectral bird image in real time, inputting the multispectral bird image into the trained integrated classifier for recognition after preprocessing and feature extraction, and determining a final bird recognition result according to a voting mechanism. According to the invention, the image acquisition, processing and identification process is more accurate and controllable.

A hydrocarbon gas detection system including a longwave infrared camera, a spectral filter, and a computation unit. The spectral filter is disposed in the light path of the camera sensor. The spectral filter is made of a material selected from the group consisting of calcium fluoride, zinc sulfide, magnesium fluoride, and silicon. The computation unit is arranged to process image data of the longwave infrared camera for the hydrocarbon gas detection.

Methods and systems for processing sequences using spectral state space models One of the methods includes, for successive time steps: processing an initial item embedding using an analysis network comprising processing layers arranged in a sequence, a first processing layer being configured to receive the initial item embedding, and to output a modified item embedding, and each other processing layer being configured to receive the item embedding output by the preceding layer and output a modified item embedding; wherein at least one of the processing layers is a spectral transform layer which, for each time step: generates a plurality of feature vectors by processing a sequence embedding using a plurality of spectral filters; multiplies the feature vectors by weight matrices, to form respective weighted feature vectors; and generates the modified item embedding for the time step including a term based on the weighted feature vectors.

The present invention discloses a reflective portable imaging and image processing method for metal mesh defect detection. The method comprises the following steps: constructing a reflective portable imaging system and combining it with a carrying motion device to capture images of the metal mesh in situ; extracting prior information about block defects and broken wire defects from the metal mesh image using a method based on spectral filtering fusion and Hough transform; inputting the captured image and the prior defect information into a low-rank decomposition model to obtain the low-rank portion, sparse portion, and noise portion of the image; and performing threshold segmentation on the sparse portion to extract defects. The method can achieve in-situ imaging measurement of the metal mesh, identify and detect various defects in the metal mesh image, and provide accurate and efficient detection results.

A system for acquiring data regarding a wound in tissue comprises at least one excitation light source configured to directly illuminate a wound with excitation light; a spectral filtering mechanism configured to permit passage of optical signals responsive to illumination of the wound and having at least one wavelength corresponding to bacterial, fungal, and / or other microorganism autofluorescence and / or bacterial, fungal, viral, and / or microbial fluorescence, the spectral filtering mechanism including a plurality of selectable filters respectively corresponding to different discrete spectral bandwidths; an optical sensor configured to detect the spectrally filtered signals; and a processor configured to receive the detected, filtered signals and to identify a fluorescent signature of bacteria in the wound based at least in part on the detected, filtered signals and to output data regarding the bacterial, fungal, viral, and / or microbial fluorescent signature.

The invention discloses an AI-driven fish raw material multi-modal digital sorting system, relates to the technical field of multi-modal data fusion and processing, and aims to realize multi-modal data real-time fusion analysis by introducing hyperspectral imaging and X-ray perspective technologies and combining a convolutional neural network, so that the fish individual feature capturing capability is remarkably improved; for fish behavior variability, a behavior uncertainty index Ui is constructed, so that the sensor sampling frequency and the convolutional neural network weight are dynamically adjusted, and the sorting accuracy and efficiency are greatly improved. Meanwhile, the system monitors water quality parameters such as turbidity, dissolved oxygen and suspended matter concentration, calculates an environmental stability coefficient Es, and adopts self-adaptive spectrum filtering and X-ray perspective technologies, so that visual interference caused by turbid water and non-uniform light is effectively inhibited, stable operation of the system under complex water quality conditions is guaranteed, sorting errors are remarkably reduced, and the sorting efficiency is improved. And the sorting efficiency and the product quality are comprehensively improved.

The invention provides a spectrum enhancement filtering metasurface method based on multi-physics field coupling, and the method comprises the steps: building a heat-force multi-physics field model of a metasurface under the incidence of high-power laser, obtaining a temperature field through calculation, and recognizing a hot spot region based on the temperature field; calculating a thermal stress field based on the temperature field, calculating refractive index variation and distribution of the metasurface material based on the temperature field and the thermal stress field, further quantifying resonant wavelength drift caused by the refractive index variation, and positioning an optical mode mismatch area; reversely designing geometric parameters of a compensation structure based on the resonant wavelength drift distance and the optical mode mismatching region; preparing a compensation type metasurface sample according to the geometric parameters, and testing the spectral response of the compensation type metasurface sample under high-power laser; based on the spectral response, the spectral enhancement filtering stability of the compensation type metasurface sample is evaluated, the problem of thermal-optical mismatch caused by high-power laser is solved, and long-term stable operation of the spectral filtering function in a severe environment is achieved.

Image sensors, imaging systems, and methods for constructing image sensors. The image sensor includes a pixel array. The pixel array includes a first photosensitive region, a second photosensitive region, a spectral router, and a spectral filter. The first photosensitive region is configured to detect visible light within a color wavelength range. The second photosensitive region includes a plurality of light scattering structures. The second photosensitive region is configured to detect infrared light. The spectral router is positioned over at least the first photosensitive region. The spectral router is configured to route the visible light within the color wavelength range to the first photosensitive region. The spectral router is also configured to route the infrared light to the second photosensitive region. The spectral filter is positioned over the spectral router. The spectral filter is configured to block visible light outside of the color wavelength range.

An integral field spectral imager has a plurality of optical homogenizers. Each optical homogenizer is in-register with a corresponding different superpixel in a superpixel array and is configured to spatially homogenize incident EMR and to pass the spatially homogenized EMR to a spectral filter in an array of spectral filters, thence to the in-register, corresponding different superpixel. Baffles are included to maximize confinement of the spatially homogenized EMR passed by a single optical homogenizer to the in-register, corresponding different superpixel so as to minimize crosstalk between superpixels. Optical homogenizers and baffles are designed to produce a pattern of homogenized EMR on a superpixel, regardless of where incident EMR is received on an optical homogenizer. Methods for using embodiments of the spectral imager in a variety of spectral bands in the EMR spectrum enable determining spectral information about incident EMR.

This invention belongs to the field of concrete pouring technology, and particularly relates to a precise control method for pile foundation concrete pouring based on multi-source sensor fusion. Addressing the problems of large measurement errors, frequent over-pouring, and significant concrete waste in traditional pile foundation pouring, this invention employs a high-frequency ultrasonic probe array coaxially fixed to the outer wall of the pouring guide pipe to uniformly elevate and scan, acquiring three-dimensional point cloud data of the entire pile foundation. After two levels of outlier removal and adaptive multi-scale spectral filtering preprocessing, combined with the expansion of the over-pouring section point cloud, a high-precision three-dimensional model of the pile foundation is constructed. Cross-sectional features at each depth are extracted to generate a pumping flow rate feedforward compensation curve, and a segmented adaptive improved PID controller is constructed with real-time concrete interface elevation and rise speed as feedback quantities to dynamically regulate the pumping flow rate. This invention achieves automated, intelligent, and precise control of the entire pile foundation pouring process, effectively improving pouring control accuracy, significantly reducing concrete waste and construction costs, and solving the measurement and pouring control problems of traditional construction.

The invention discloses a disease analysis system based on an improved hyperbolic graph neural network model, which combines hyperbolic space embedding, high-order spectral filtering and an adaptive mechanism to improve the expression and reasoning ability of multi-scale structural features in a medical knowledge graph. The system can extract richer structural features in a frequency domain by introducing a high-order spectrum filter constructed based on a Legendre polynomial; automatically adjusting the receptive field range of the filter to adapt to different graph structures by using a self-adaptive order; and disease node classification and relation prediction are realized through logarithm mapping and a neural classifier. Experimental results show that compared with an existing method, the method has higher accuracy and lower loss value in disease map node classification and link prediction tasks, a structured medical knowledge system can be optimized, medical map information can be complemented, potential disease association and drug connection can be found, and the method has good clinical application prospects.

The application provides an X-ray ultrafast imaging system and method based on radiation conversion and spectral filtering, which solves the problems of poor universality, low time resolution or limited number of frames in existing X-ray ultrafast imaging technology. The system comprises an X-ray coupling module for coupling target X-ray signals to image on a semiconductor chip module, a semiconductor chip module for converting the X-ray intensity space-time distribution into the chip refractive index space-time distribution, a chirped pulse light generation module, a chirped pulse light coupling module for irradiating linear chirped pulse light generated by the chirped pulse light generation module to the semiconductor chip module and coupling the pulse light reflected by the semiconductor chip module into a phase extraction module, the phase extraction module, a spectral filtering frame reading module for imaging the linear chirped light intensity space-time distribution signal output by the phase extraction module into the data acquisition module, the data acquisition module and an image processing module for processing the image output by the data acquisition module.

Provided is a portable biosensor that includes a sample filter cartridge, a filter collector, an optical sphere, an electromagnetic radiation emitter, a photo-detector, a processor, a signal display, a vacuum pump, and a power supply. The sample filter cartridge selectively removes small molecules to minimize spectral interference in the detection signal. The sample is concentrated onto the filter collector and subjected to illumination by the electromagnetic radiation emitter, producing Raman-scattering. The optical sphere collects and distributes the Raman-scattering shifts, which then pass through a spectral filter to produce spectral filtered scattering, which is then reflected by the concave holographic flat-field grating onto the photo-detector. The data is displayed graphically to provide the Raman-scattering shift data. The data is compared with a database for sample identification. The device is contained within a housing that is small enough to be easily transported for field use.

In certain embodiments, an ophthalmic surgical system for viewing an eye includes an ophthalmic microscope and a laser device. The ophthalmic microscope receives light reflected or scattered backwards from within the vitreous of the eye in order to provide an image of an object within the vitreous. The ophthalmic microscope includes a slit illumination source (which includes a light source and an optical element), a spectral filter, and oculars. The slit illumination source illuminates the eye with light, where the light source provides the light, and the optical element directs the light into the eye. The spectral filter filters out red spectral components of the light. The oculars receive the light from the eye in order to provide the image of the object. The laser device generates a laser beam to direct towards the object within the eye.

A high-performance single-shot contrast measurement device with real-time self-verification of accuracy is characterized in that the sampling light of the single-shot contrast measurement device is obtained based on spectral broadening and spectral filtering in a self-phase modulation process, so that the sampling light has high contrast, high energy, and a large difference from the central wavelength of the incident light, and good stability; at the same time, the sampling light introduces a series of intensities through a pulse replication unit to be attenuated in sequence, and is offset at equal intervals in position. The sampling light is also evenly spaced in time for self-verification of the measurement accuracy of the measurement device. This invention realizes the characteristics of single-shot contrast measurement with high measurement dynamic range, wide time window, high time resolution, high measurement fidelity, simple and compact device, and real-time verification of the accuracy of measurement results, providing better support for improving the contrast of ultra-strong and ultra-short laser pulses and related laser-matter interaction experimental research.

The invention relates to the field of ultra-high-definition image restoration, in particular to an ultra-high-definition image restoration method based on grouping Chebyshev spectral filtering, ultra-high-definition image restoration is carried out by constructing an ultra-high-definition image restoration model, and the ultra-high-definition image restoration model is constructed by the following steps: constructing a ChebSpecic-Net model; the ChebSpec-Net model comprises a first convolution module, an encoder, a bottleneck layer, a decoder, a second convolution module and a first residual connection module which are connected in sequence; the encoder comprises three SpectroTrans modules and three down-sampling modules, the decoder comprises three SpectroTrans modules and three up-sampling modules, and jump connection fusion is arranged between the encoder and the decoder to maintain spatial detail information; according to the method, a symmetric multi-scale coding-decoding architecture is constructed, progressive feature extraction and reconstruction are carried out at different resolution levels through a SpectroTrans module, and effective fusion of global-local features is realized while spatial details are kept in cooperation with up-sampling and jump connection.

A monolithic LED IC die can include multiple emission regions independently operable by applying independent electrical input signals, such as to independently control light output from different individual ones of the multiple emission regions. Optics can include different spectral filters applied to the different light outputs from the different individual ones of the multiple emission regions, such as to define different spectral bands output by the different spectral filters. These different spectral bands can be differently encoded, and the encoded light can be used for enhanced spectroscopy. Additionally or alternatively, the different individual ones of the multiple emission regions can be selectively energized, such as to provide a tunable light source via the different spectral bands output by the optics. The monolithic LED IC die with the multiple emission regions can make the optics more compact, such as for a wearable or other compact device for spectroscopic measurement or analysis.

The application relates to a non-labeled far-field super-resolution microscopic spectral imaging system and an implementation method, which utilizes the characteristics of a plane achromatic super-resolution lens chip to generate a far-field super-resolution focus point, combines a dynamic adjustable spectral filtering device, does not sacrifice the spatial resolution of spectral imaging, builds the non-labeled far-field super-resolution microscopic spectral imaging system, and overcomes the problem that the existing super-resolution microscopic imaging system cannot obtain spectral information of the target physical and chemical characteristics.

The application discloses a hyperspectral remote sensing image recognition method and device based on spectral space feature coupling, and utilizes different linear spectral filters to perform feature extraction on the whole hyperspectral remote sensing image, so that multi-class spectral features are obtained. Compared with the traditional technology, the application does not need to perform spectral dimension reduction, thereby avoiding the problem that the traditional technology weakens the subtle spectral information and high-order spectral correlation contained in the hyperspectral data. Meanwhile, the application takes the minimization of image background energy as an objective function to optimize the optimal real spectral feature vector of each linear spectral filter to the target class. Based on this, when the constructed linear spectral filter is used for feature extraction, the background energy can be minimized while the target spectral response is maintained and enhanced, so that the spectral clutter and noise in the complex environment are suppressed, and thus the detection precision of the model in the complex environment background can be improved.

The invention aims to provide a target detection method and system for suppressing marine radar image sequence clutters based on time-space domain Hough transform, and the method comprises the steps: firstly removing sea clutter spectrum energy through employing a frequency domain and wave number domain combined filter based on a dispersion relation, and then intercepting a spectrum center region; the method comprises the following steps: firstly, performing clutter suppression on an image sequence, acquiring target frequency spectrum parameters by using Hough detection to establish a clutter frequency spectrum filter so as to realize further clutter filtering, finally performing generalized extreme value distribution modeling on the image sequence subjected to clutter suppression to obtain mu, sigma and xi values conforming to data background clutters, and performing target point detection by using a rejection inclusion detector. The algorithm is verified by using the real data of the X-band marine radar, and the method can effectively suppress the strong clutter signal, thereby enhancing the signal-to-noise ratio of the image, and further improving the target detection probability under the strong sea clutter condition.

A measurement system with active illumination using pulsed semiconductor diodes and a detection system comprising a camera imager with lenses and spectral filters that is synchronized to the pulsed diodes. The light generated by the diodes may comprise visible or near-infrared wavelengths. The measurement system may also comprise a time-of-flight sensor or a beam splitter to separate the diode light into a plurality of spatially separated lights. The detection system may be configured to receive light reflected from tissue comprising skin and may be configured to perform a differential measurement between a hand and another region of tissue. The measurement system including a processor may be configured to identify veins in the hand or measure oxygen level in blood. The system may be used to identify an object or to measure physiological parameters. The system may also be coupled to a cloud service and use artificial intelligence in making decisions.

Provided is an imaging system that can reduce noise in received infrared light data. The imaging system includes a light source that emits infrared light, and an imaging device that images an object irradiated with the infrared light emitted from the light source, wherein: the imaging system includes a first polarizer which is provided between the light source and the object and which polarizes the infrared light emitted from the light source; the imaging device includes, from the infrared light incident side, an absorption type second polarizer that polarizes the infrared light, and an image sensor; the image sensor includes a spectral filter layer and an imaging element; the spectral filter layer includes a multi-bandpass filter having transmission bands in the visible light band and a part of the infrared light band; and the full width at half maximum of the transmission band in the infrared light band of the multi-bandpass filter is 60 nm or less.

A device for detecting a mixture ratio of two components of a textile fabric contains a radiation source for transmitting electromagnetic radiation in a spectral band in the direction of the textile fiber structure, a radiation sensor for receiving at least a part of the electromagnetic radiation, and a spectral filter with spectral properties in the spectral band for filtering at least one part of the electromagnetic radiation. The transmittance of the spectral filter in the spectral band has at least one local maximum and at least one local minimum. The spectral properties of the spectral filter in the spectral band are adapted to the spectral properties of the radiation source and each of the two components such that a radiation intensity received by the radiation sensor is a monotonous function of the mixture ratio of the two components. The device is simple in design and allows the use of spatially resolving imaging radiation sensors.

The invention discloses a hyperspectral remote sensing image recognition method and device based on spectral spatial feature coupling, different linear spectral filters are utilized to perform feature extraction of the whole hyperspectral remote sensing image so as to obtain multi-category spectral features, and compared with a traditional technology, the hyperspectral remote sensing image recognition method does not need spectral dimension reduction, and is high in recognition efficiency. Therefore, the problem that the correlation between fine spectral information and high-order spectrum contained in the hyperspectral data is weakened in the traditional technology is avoided; meanwhile, minimization of image background energy is used as a target function to optimize the optimal real spectral feature vector of each linear spectral filter for the target category, so that when the constructed linear spectral filters are used for feature extraction, the background energy can be minimized while the target spectral response is maintained and enhanced, and the target spectral response is improved. Therefore, spectral clutter and noise in a complex environment are suppressed, and the detection precision of the model in a complex environment background can be improved.

To provide a spectroscopic analysis device or a spectroscopic analysis method that obtains a spectrum of an object to be analyzed by a transmission wavelength-tunable optical filter using a Fabry-Perot (FP) structure, and can detect the actual transmission peak wavelength of the transmission wavelength-tunable optical filter.SOLUTION: A spectroscopic analysis device comprises an imaging element, a transmission wavelength-tunable FP optical filter A, and a film thickness gradient FP spectral filter B. A part of incident light transmits through both the optical filter A and the spectral filter B and reaches the imaging element, and the remaining incident light reaches the imaging element without transmitting through the spectral filter B. A spectroscopic analysis method includes, in spectroscopic analysis of incident light of the optical filter A, making a part of light transmitted through the optical filter A incident on the spectral filter B, and detecting the transmission peak wavelength of the optical filter A using, as an index, the transmission peak wavelength of the spectral filter B or the transmission peak wavelength of the optical filter A of a part of incident light that is dispersed and transmitted by the spectral filter B and is made incident.SELECTED DRAWING: Figure 7

This invention provides a quantum algorithm utilizing noise-induced spectral filtering to optimize a target quantum circuit and obtain its global optimal solution. The algorithm includes: S1, constructing a noisy proxy model with added quantum noise for the target quantum circuit to be optimized, used to proxy the evolution of quantum states affected by noise after each quantum logic gate operation; S2, performing a first gradient descent optimization on the noisy proxy model to obtain pre-trained circuit parameters for the target quantum circuit; S3, loading the pre-trained circuit parameters into a noise-free or low-noise environment simulating the target quantum circuit to complete parameter transfer; S4, in the environment simulating the target quantum circuit after parameter transfer, performing a second gradient descent on the circuit parameters based on the loss function of the target quantum circuit until convergence to obtain the global optimal solution for the target quantum circuit.

A polarization spectral filter is provided, comprising: a first reflector and a second reflector, which are arranged to face each other in a first direction; and a grating layer, which is arranged between the first reflector and the second reflector. The grating layer includes a plurality of first grating elements and a plurality of second grating elements, and the plurality of first grating elements and the plurality of second grating elements are alternately arranged in a second direction perpendicular to the first direction. The plurality of first grating elements include a first dielectric material having a first refractive index. The plurality of second grating elements include a second dielectric material having a second refractive index different from the first refractive index.