40 results about "High resolution spectra" patented technology

The invention provides an underwater target identification method and system based on 4K visible light polarization imaging, and relates to the technical field of underwater target identification. High-resolution spectral intensity information and polarization physical characteristics of a target are synchronously captured by using a pixel-level registration RGB and polarization four-dimensional light field tensor coding technology; the limitation of information loss of single-mode data in a low-illumination or high-turbidity scene is overcome; the polar coordinate symmetry design of the annular direction sensitive convolution kernel is combined with the polarization degree matrix decomposition technology of the Fresnel reflection law to accurately quantify the optical reflection characteristic difference of the material; based on a cross-modal attention mechanism, dynamically learning a correlation weight of a spatial feature and a polarization feature, and strengthening a joint response of a target edge contour and an internal texture; a lightweight recognition network architecture is adopted, a polarization sensitive convolution kernel and a dynamic channel re-parameterization module are integrated, parallel efficient reasoning of target position, category and material information is achieved, and accurate recognition of an underwater target is achieved.

The invention discloses a calibration device with a spectrum self-calibration function and a high-resolution spectrum calibration method thereof. The device comprises a narrow-band light source, a broadband light source, an optical fiber isolator, a coupler, an interference system, a multi-way switch, an FP (Fabry-Perot) cavity, a collimator, an orthogonal dispersion system and a computer, wherein the orthogonal dispersion system consists of a cylindrical lens, a reflector, a virtual phase array, a grating, a focusing lens and an industrial camera; according to the device, different light source paths are gated, FP cavity modulation and orthogonal dispersion system light splitting are utilized, and an industrial camera is combined to receive light signals. According to the method, the mapping relation between pixels and wavelengths can be established, the two-dimensional spectrum is compressed into the one-dimensional calibration spectrum through light intensity modulation and normalization processing, the calibration process of the orthogonal dispersion system is simplified, and the measurement precision is improved; and system drift can be compensated in real time through self-checking calibration, and the reliability of a measurement result is ensured, so that accurate calibration and measurement of a high-resolution spectrum can be realized.

The invention discloses a one-dimensional ultra-wide field-of-view ultra-high spectral resolution dispersion coherent imaging spectrometer, which belongs to the technical field of spectral imaging, and comprises a first microlens array used for obtaining incident light of a one-dimensional ultra-wide field-of-view in a horizontal plane; the plurality of optical fibers are used for transmitting incident light of a one-dimensional ultra-wide field of view; the second micro lens array is used for collimating incident light from each optical fiber into broadband parallel light beams; the grating beam splitter interferometer is used for dispersing the broadband parallel light beams into a plurality of narrow-band parallel light beams with different propagation directions; the cylindrical lens is used for converging the two paths of coherent light of each narrow-band parallel light beam to a target block of the detector, and converging the narrow-band parallel light beams with different propagation directions to different target blocks respectively; and the detector is used for obtaining a continuous broadband ultra-high resolution spectrum according to the two paths of coherent light received by each target block. According to the invention, a one-dimensional ultra-wide field of view is obtained in a horizontal plane, and ultra-high spectral resolution can be obtained.

The invention discloses a spectral super-resolution model training method, a spectral super-resolution measurement method and a spectral super-resolution measurement device. The method comprises the following steps: acquiring multiple groups of low-resolution spectral data and corresponding high-resolution spectral data; constructing a spectral super-resolution model fusing the three-dimensional convolutional layer and the spectral physical constraint term; and training the spectral super-resolution model by taking each group of low-resolution spectral data as input and taking the group of high-resolution spectral data as a label as a training sample in sequence until an error between the high-resolution spectral data output by the spectral super-resolution model and the high-resolution spectral data as the label meets a preset threshold value. Through the spectrum super-resolution model, the efficiency of spectrum measurement can be improved in a disguised manner, and the accuracy of parameter inversion can be ensured.

Methods and systems for using multiple hyperspectral cameras sensitive to different wavelengths to predict characteristics of objects for further processing, including recycling, are described. The multiple hyperspectral images can be used to predict higher resolution spectra by using a trained machine learning model. The higher resolution spectra may be more easily analyzed to sort plastics into a recyclability category. The hyperspectral images may also be used to identify and analyze dark or black plastics, which are challenging for SWIR, MWIR, and other wavelengths. The machine learning model may also predict the base polymers and contaminants of plastic objects for recycling. The hyperspectral images may be used to predict recyclability and other characteristics using a trained machine learning model.

The invention discloses a temperature-pressure-resistant vibration methane carbon isotope detection system for oil and gas logging, which belongs to the technical field of oil and gas logging and comprises a gas sample pretreatment module, an optical sensing module, a driving and temperature control module and a core control and algorithm module. The core control module is realized by an FPGA (Field Programmable Gate Array) and is integrated with a self-adaptive multi-resolution scanning and compressed sensing reconstruction algorithm. The method comprises the following steps: performing current segmented scanning and wavelength modulation on the laser; light path anti-vibration coupling is realized through closed-loop control of the MEMS galvanometer; acquiring sparse sampling spectrum data; reconstructing a high-resolution spectrum by using compressed sensing; and inversing CH4 and CH4 concentrations by adopting Voigt linear fitting, and calculating a delta C value. The precision, the speed and the long-term stability of methane carbon isotope detection in a logging site temperature-pressure vibration coupling disturbance environment are remarkably improved.

The application provides an underwater target recognition method and system based on 4K visible light polarization imaging, and relates to the technical field of underwater target recognition.The application uses pixel-level registration RGB and polarization four-dimensional light field tensor encoding technology to synchronously capture high-resolution spectral intensity information and polarization physical characteristics of a target, overcomes the limitation of information loss of single modal data in low-light or high-turbidity scenes, designs polar coordinate symmetry of a ring-shaped direction-sensitive convolution kernel, combines polarization degree matrix decomposition technology of the Fresnel reflection law, accurately quantifies the optical reflection characteristic difference of a material, dynamically learns the correlation weight of spatial features and polarization features based on a cross-modal attention mechanism, strengthens the joint response of target edge contours and internal textures, adopts a lightweight recognition network architecture, integrates a polarization-sensitive convolution kernel and a dynamic channel reparameterization module, realizes parallel and efficient inference of target position, category and material information, and realizes accurate recognition of underwater targets.

The invention discloses a spectrum super-resolution method and system based on an FP cavity and deep learning, and the method comprises the steps: S1, carrying out the initialization of spectrum collection, and selecting light with a specific wavelength after the light is acted with a target detection object; s2, performing photoelectric conversion and digitization to generate low-resolution original discrete spectrum data of corresponding wavelengths; s3, continuous spectrum scanning is carried out, and original discrete spectrum data collection of the whole target wave band is completed; and S4, performing super-resolution spectrum reconstruction, and judging whether cyclic reconstruction is performed or not based on a reconstruction data quality evaluation result until the quality is qualified. According to the method, an accurate mapping model from a low-resolution spectrum to a high-resolution spectrum is established through a pre-trained deep neural network, and an original spectrum which is collected by an FP cavity and is limited by the theoretical limit optical resolution of the FP cavity can be reconstructed into a super-resolution spectrum of which the resolution remarkably exceeds the theoretical limit. The problem that the resolution of an FP cavity in a long-wave region is sharply reduced is effectively solved, and the full-wave-band uniform high resolution is realized.

A method for detecting structural variations in chromosomes by labeling single-stranded chromatids with different colored probes is disclosed. The hybridization patterns of the labeled probes generate spectral profiles that enable high-resolution detection of structural variations, facilitating the distinction between benign and deleterious structural variations. Furthermore, the spectral profiles provide information about complex structural variations that may result from more than one rearrangement of chromosomal segments. The spectral profiles can be used to generate data tables, which can then be subjected to node analysis to identify structural features of interest.

The invention relates to the technical field of marine environment monitoring, in particular to a marine oil spill monitoring method and system based on a crude oil spectrum. Comprising the following steps: S1, identifying N marine oil spill positions by using a fuzzy reasoning model, and distributing monitoring points for the N marine oil spill positions to form a first monitoring sequence; s2, K important oil spill positions and monitoring points corresponding to the important oil spill positions are optimized through a genetic algorithm, a second monitoring sequence is formed, and K is smaller than N and is a positive integer larger than or equal to 1; s3, calculating the time when the crude oil reaches the sea surface and marking a path; a high-resolution spectrometer is used for collecting spectral data in visible light, near-infrared and middle-infrared wave bands, and features are screened after preprocessing. According to the method, the ocean oil spill monitoring path is optimized through fuzzy reasoning and a genetic algorithm, spectral data are predicted in combination with a Transform model, the path and the model are dynamically corrected, and the monitoring precision and the response efficiency are improved.

The present invention relates to the field of optical lenses, and provides a mid-wave infrared spectral imaging lens. From the object surface to the image surface, it sequentially includes a first lens, a second lens, a third lens, a Dewar window, and a filter, which are arranged coaxially; the first lens, the second lens, and the third lens are all aspherical lenses; the first lens has a positive optical power, and the focal length of the first lens satisfies 245 mm ≤ f1 ≤ 250 mm; the second lens has a negative optical power, and the focal length of the second lens satisfies -30 mm ≤ f2 ≤ -25 mm; the third lens has a positive optical power, and the focal length of the third lens satisfies 20 mm ≤ f3 ≤ 25 mm. The solution of this application reduces the number of lenses by introducing aspherical lenses, and solves the defect that the existing mid-wave infrared spectral imaging lens is difficult to simultaneously meet the requirements of large field of view, high energy utilization rate, and high-resolution spectral imaging.

Molecular rotation resonance (MRR) spectroscopy is a structure-specific high-resolution spectroscopy technique that can identify chemical species, including enantiomers, that cannot be distinguished by other analytical techniques. In MRR spectroscopy measurements, a gas phase sample is injected into a vacuum chamber in which the gas phase sample is excited with millimeter wave or microwave radiation, and in response, the gas phase sample emits a free induction pulse (FID). The spectrum of the FID pulses provides information about the chemical structure of the sample. In MRR ratio method measurements, the sample is irradiated simultaneously by two excitation pulses at different frequencies (e.g., broadband pulses and narrowband pulses of different frequency bands or narrowband pulses at different frequencies). The pulses stimulate simultaneous or overlapping FID emissions of different components of the sample. The spectra of these FID emissions are compared, resulting in a ratio of the components in the sample.

An anti-interference image reconstruction method, apparatus, medium, and electronic device are disclosed, relating to the fields of optoelectronic imaging and target detection technology; achieving anti-fish scale light and anti-backlight imaging under complex lighting environments. The anti-interference image reconstruction method includes: acquiring the infrared radiation light field of the target scene through an infrared optical lens; filtering interference light from the infrared radiation light field using a metasurface modulation module; acquiring multi-dimensional light field information after passing through the metasurface modulation module using an infrared imaging detector; the metasurface modulation module employs GSST phase change material, controlling the infrared spectral band and polarization state through switching between crystalline and amorphous states; and reconstructing the acquired multi-dimensional light field information using a multi-dimensional light field reconstruction module to obtain a high-resolution spectral image.

Methods and software applications for transmitting high-resolution spectral curve data to a tinter for generating a tint formula usable to custom-tint a base paint or coating to match the color of a sensed surface. The high-resolution spectral curve data is derived from low-resolution or wideband spectral data obtained via a low resolution or wideband spectrophotometer. Additional user information, order information, or location information may be transmitted to the tinter.

The invention discloses a 250-1700 nanometer six-wave-band switchable high-resolution thin-plate spectrometer, and belongs to the technical field of spectral measurement, the 250-1700 nanometer six-wave-band switchable high-resolution thin-plate spectrometer comprises a plurality of measurement assemblies which are sequentially arranged in the x direction, each measurement assembly comprises a micro lens, an optical filter, a plane transmission grating and a detector, the micro lens collimates incident light into parallel light beams, and the parallel light beams are transmitted to the optical filter; the optical filter transmits light beams in a specific wave band range in the parallel light beams; the plane transmission grating diffracts the filtered parallel light beams to generate primary diffraction light beams; a pixel array of the detector is divided into a plurality of blocks arranged in the y direction, and high-resolution spectral information, collected by the micro lens, of a detected object in a specific wave band is obtained in real time according to target blocks irradiated by first-order diffraction light beams with different wavelengths in the specific wave band. According to the spectrograph, the combination of all the measuring components can cover the ultra-wide wave band of 250-1700 nanometers, and switchable independent measurement or simultaneous measurement of multiple wave bands is supported.

This invention provides a food contamination detection method based on multi-wavelength spectrophotometry. In this embodiment, a tunable multi-wavelength light source system emits light within a series of wavelengths onto a food sample, generating a spectral response. This spectral response is collected using a high-resolution spectrometer to form a multi-dimensional spectral image. A deep learning algorithm is then used to analyze and identify subtle spectral differences between natural components and potential contaminants in the food sample, obtaining preliminary identification results. An adaptive wavelength selection mechanism is implemented to dynamically adjust the wavelength output of the light source, obtaining spectral response data. This data is then compared with a pre-set food safety standard database to generate a food safety assessment report. The food safety assessment report includes contaminant types and concentration distribution maps. The technical solution provided by this invention enables highly efficient and accurate identification of natural components and potential contaminants in food samples, significantly improving the sensitivity, specificity, and accuracy of contaminant detection.

This invention discloses an endocrine rhythm-driven PPO full-spectrum intelligent dimming system, comprising a multi-dimensional data perception layer, an edge computing and core decision-making layer, and a light control execution layer. The multi-dimensional data perception layer includes a front-end high-resolution spectral sensing sensor module and a wearable device interface module; the edge computing and core decision-making layer includes a standardized feature dataset architecture unit, an endocrine multi-axis coupling prediction unit, and an AI decision model; the light control execution layer includes a five-channel visible light driving controller and a full-spectrum LED light-emitting module. This invention can offset rhythm deviations caused by environmental interference light sources in practical application scenarios, ensuring that the composite light entering the eye always conforms to the preset physiological regulation target, achieving the purpose of precise dimming, and can provide deep-level photoneurophysiological gains, synergistically improving the user's sleep quality and wakefulness.

The invention belongs to the technical field of spectrum calibration, and discloses a tunable optical frequency comb spectrum calibration method, which adopts a repetition frequency adjustable optical frequency comb as a calibration source, realizes flexible adjustment of comb tooth intervals by adjusting repetition frequency, and can accurately meet the requirements of spectrometers with different resolutions. The method mainly comprises the following steps: generating an offset frequency locking repetition frequency adjustable optical frequency comb, recording pixel positions of comb teeth of the optical frequency comb on a spectrometer CCD, establishing a wavelength-position mapping relation, optimizing a calibration model by applying machine learning, and carrying out error analysis and correction. Compared with a traditional spectrum calibration method, the method has the advantages of high-precision calibration, wide spectrum coverage range, flexible comb tooth intervals and adaptive optimization, is suitable for the fields of high-resolution spectrum analysis, scientific research and the like, and is particularly suitable for spectrum application scenes needing accurate wavelength calibration.

The invention discloses a plasma chyle degree detection method and system based on a spectrum principle, and relates to the technical field of medical examination, and the method comprises the following steps: using a multi-light source combination system to emit light in a wide spectral range covering ultraviolet light, visible light and near-infrared light to irradiate a to-be-detected plasma sample; the method comprises the following steps: synchronously acquiring absorption, scattering and transmission data of a plasma sample to light with different wavelengths through a high-resolution spectrum sensor to obtain multispectral data; and performing feature extraction on the acquired multispectral data by using a machine learning algorithm. According to the plasma chyle degree detection method and system based on the spectrum principle, richer information, such as detection of interaction between protein and nucleic acid and chyle particles by ultraviolet light and analysis of lipid structures by near-infrared light, can be obtained by utilizing specific response of different spectrum regions to components such as protein, nucleic acid and lipid in plasma and chyle particles. The multi-spectrum collaborative acquisition mode is a breakthrough of traditional single-spectrum detection.

The application provides an external cavity tuning semiconductor laser and a uniform wave number synchronous output method thereof, rapid and accurate modulation of the angle of a feedback light beam is realized through rapid deflection of an optical galvanometer, and the method specifically comprises the following steps: synchronously collecting the deflection angle of the optical galvanometer and the instantaneous output spectrum, accurately calculating the center wavelength of each sampling point by using a Gaussian fitting method, converting the center wavelength to the wave number domain for uniform processing, and obtaining the optimized driving curve of the deflection angle of the optical galvanometer changing with time through reverse calculation, so that the laser is finally synchronously and rapidly output according to the uniform wave number; the application can effectively overcome the deficiencies of traditional motor driving or piezoelectric ceramics in terms of precision, tuning speed and scanning stroke, significantly reduce the hardware cost of the core component, and has a wide application in the scenes of coherent tomography, high-resolution spectral analysis and precise laser radar.

The application discloses a kind of dual-channel hyperspectral imaging device and method based on Sagnac interferometer.The incident light from target collimates after passing through pre-imaging objective, diaphragm and collimating objective, and is incident to Wollaston prism again after passing through polarizer, and Wollaston prism shears incident light into different direction o light and e light, and after passing through Sagnac waveband division shear structure, different waveband o light and e light produce different lateral shear amount, and are emitted along different directions, pass through polaroid array and filter array, and finally form spatially separated two different waveband interference images on area array detector by post-imaging objective.The application can obtain two groups of interference images under different wavebands by once push scanning, and realizes high-resolution spectral imaging under wide waveband range.

Methods and systems for using multiple hyperspectral cameras sensitive to different wavelengths to predict characteristics of objects for further processing, including recycling, are described. The multiple hyperspectral images can be used to predict higher resolution spectra by using a trained machine learning model. The higher resolution spectra may be more easily analyzed to sort plastics into a recyclability category. The hyperspectral images may also be used to identify and analyze dark or black plastics, which are challenging for SWIR, MWIR, and other wavelengths. The machine learning model may also predict the base polymers and contaminants of plastic objects for recycling. The hyperspectral images may be used to predict recyclability and other characteristics using a trained machine learning model.

The embodiment of the application provides a kind of millimeter wave and sub-terahertz signal spectrum identification method and system based on coherent detection, belong to signal spectrum analysis, technical field.The method comprises: receiving the signal to be measured and modulating with optical carrier, obtain modulated optical signal;The modulated optical signal and the swept local oscillator light are coherently beat, and the beat electric signal is obtained;The voltage time sequence of the beat electric signal is acquired, and the reconstructed spectrum is obtained after bandpass filtering and root mean square envelope extraction;According to the reconstructed spectrum, the signal frequency is calculated by carrier positioning and Lorentz fitting;According to the reconstructed spectrum, the signal amplitude is predicted based on the pre-trained machine learning inversion model.The application can be reconstructed based on the characteristics of high-resolution spectrum of coherent detection, convert millimeter wave / sub-terahertz electromagnetic signal into spectral information that can be analyzed by low-bandwidth electric detection and digital signal processing system, realize single frequency identification, multiple amplitude inversion.

The invention relates to the technical field of ship optical characteristics, and discloses a ship visible light characteristic simulation method, system and device and electronic equipment, and the method comprises the steps: carrying out the high-resolution spectrum calculation of a background environment based on an atmospheric transmission model; determining the reflected light distribution condition of the surface of the ship according to the reflection characteristics of the surface material of the ship; and based on the grid system, performing reverse light tracing according to the distribution condition of the reflected light, and calculating the visible light coupling radiation characteristics of the ship and the background environment. Through an atmospheric transmission model, surface material analysis and reverse light ray tracing, full-path simulation from a light source to a detector is realized. By means of high-resolution spectrum calculation and ship surface material analysis, the reflected light distribution condition of the ship surface can be more accurately determined, reverse light tracing is carried out according to the reflected light distribution condition, only effective light can be tracked, the invalid calculation amount is reduced, and therefore simulation precision and simulation efficiency are improved.

The invention provides a marine steel laser-arc hybrid welding arc spectral feature extraction method which comprises the following steps: step 1, laser-arc hybrid welding spectral signal acquisition: a high-resolution spectrometer is matched with double optical fiber probes to synchronously acquire signals of corresponding channels, and cross interference of different wavebands is eliminated through grating light splitting; step 2, noise reduction processing of the spectral signal: adopting a multiplicative scatter correction (MSC) algorithm to carry out noise reduction processing; step 3, spectral signal feature extraction: extracting electron density and electron temperature features respectively; according to the marine steel laser arc hybrid welding arc spectral feature extraction method, the arrangement of the extraction method can be optimized, and the reliability and accuracy of spectral feature extraction are enhanced.

The invention concerns an apparatus for scanning the optical properties of materials using a stationary sample stage and a dual-axis rotational system. The apparatus includes motors for azimuthal and polar rotation, supporting an optical system with adjustable lenses and filters to collect data from multiple angles. This design is particularly advantageous for photo-excited materials using linearly polarized sources, as it maintains static pump polarization, eliminating the need for additional motors or optical elements to align the pump with the sample's rotation. This avoids complications with halfwave plates and broadband retarders, which may not preserve linear polarization across all wavelengths. The modular system accommodates various detectors, ensuring versatility while enabling precise, high-resolution spectral imaging. The stationary sample stage prevents alignment issues and distortion, providing consistent and accurate measurements of materials' optical properties across a range of experimental setups.

The application discloses an application of a multi-modal sensing recognition method in coal gangue separation and relates to the technical field of intelligent vision, which comprises the following steps: collecting a multispectral image, a high-speed image and a visible light image of a target scene, completing time sequence alignment in the same field of view, and obtaining an original multi-modal sensing set; sending the original multi-modal sensing set into an encoding sensing imaging link, performing spatial encoding, aperture division, light collection and gating time sequence arrangement, and obtaining an encoding observation data packet and a spectral image cube; and performing image sparse representation, image prior modeling and calculation reconstruction on the encoding observation data packet and the spectral image cube, and obtaining a high-resolution spectral image, a clear texture image and a motion frame sequence; through the image sparse representation, the image prior modeling and the calculation reconstruction, the application improves the distinguishable ability of a target region in a spectral band detail, an outline boundary and a continuous motion trajectory.

The application discloses a high-resolution spectrometer optical system for Raman spectrum detection, and solves the problems of high cost, complex structure and low utilization rate of image enhancement target surface of an existing spectrometer optical system, and specifically comprises a slit, a collimating mirror group, a spectroscope group, a focusing mirror group and an image sensor which are sequentially arranged along an outgoing direction of the slit on a light path of to-be-detected light; the slit is used for receiving the to-be-detected light and limiting the spot size of the to-be-detected light in a spectral dimension; the collimating mirror group is used for collimating the to-be-detected light passing through the slit into parallel light; the spectroscope group is used for dispersing the collimated parallel light according to wavelengths; the focusing mirror group is used for focusing the dispersed to-be-detected light to the image sensor; a target surface of the image sensor is located at a focal point of the focusing mirror group to receive the focused to-be-detected light; a distance TTL from the slit to the target surface of the image sensor satisfies 0.3<=f / TTL<=0.6, wherein f is a focal length of the focusing mirror group.

This invention discloses a super-resolution mosaic spectral image re-optimization method based on explicit observation consistency constraints. It primarily addresses the technical problem that existing mosaic spectral image reconstruction and super-resolution processing methods mainly focus on spectral image domain optimization, lacking explicit observation consistency constraints to ensure that the reconstructed result can return to the original observation after the mosaic imaging process. This invention uses the original mosaic image as a basis, obtains the current high-resolution spectral image from it, maps the current high-resolution spectral image to a predicted mosaic observation image, and constructs observation consistency constraints using the differences between the original mosaic image and the predicted mosaic observation image. It then re-optimizes the initial high-resolution spectral image result through iterative correction using residual backprojection, ensuring that the final output meets the mosaic spectral observation consistency requirements while improving spatial detail, thereby enhancing the reliability, stability, and interpretability of the reconstruction results.