94results about "Methods for obtaining spatial resolution" patented technology

A sensor comprises a transducer substrate formed of a photo-acoustically sensitive material and having a receiving surface and an absorptive layer coupled to the transducer substrate receiving surface that detects broadband electromagnetic (EM) radiation.

A method for the spatially resolved measurement of the birefringence distribution of a cylindrically symmetrical blank (2) made from an optical material transparent to at least one wavelength λ_B between 180 nm and 650 nm, in particular at 193 nm, including: irradiating the blank (2), arranged in a container (4) with an immersion fluid (5), at a jacket-side measurement position (MP) using a measuring light beam (9) which runs in a measuring direction (Y) preferably perpendicular to the axis of symmetry (S) of the blank (2), as well as varying the jacket-side measurement position (MP) by moving the measuring light beam (9) and the blank (2) relative to one another in two directions (X, Z) perpendicular to the measuring direction (Y) for the purpose of spatially resolved measurement of the non-axial birefringence distribution of the blank (2).

Thermopile-based detection and monitoring/control systems are described, in applications such as inferring concentration of a multicomponent gas by sensing a tracer gas therein, utilizing fiber optic cables to provide multiple sensing paths in a cell, utilizing a modulated IR source switched in on/off cycles, verifying chemical reagent identities, and sensing of effluent following discharge from a contamination removal 8 element or cold trap. A thermopile infrared (TPIR) detector of highly compact character is described for such applications, and permits monitoring of species that may be problematic or otherwise deleterious in such environments. In one implementation, light source modulation and signal processing techniques are employed to improve signal to noise ratio and minimize calibration and complexity of the TPIR detector.

Methods of obtaining dopant and damage depth profile information are disclosed using modulated optical reflectivity (MOR) measurements. In one aspect, the depth profile is constructed using information obtained from various measurements such as the junction depth, junction abruptness and dopant concentration. In another aspect, a full theoretical model is developed. Actual measurements are fed to the model. Using an iterative approach, the actual measurements are compared to theoretical measurements calculated from the model to determine the actual depth profile.

Disclosed is a method of obtaining a spectral image of each of a plurality of predetermined chemical species in a sample, comprising: (a) illuminating the sample with a first plurality of photons to produce a second plurality of photons; (b) collecting the second plurality of photons and producing a plurality of images of the sample therefrom, each of said images comprising a frame consisting essentially of a plurality of pixels; (c) for each of the predetermined chemical species, identifying at least one wavelength range at which the chemical specie exhibits a unique absorption of radiation; (d) identifying at least one wavelength range at which none of the predetermined chemical species exhibits an absorption of radiation; (e) in each of the image frames, identifying which of the pixels do not contain any of the predetermined chemical species; (f) in each of the image frames, identifying which of the pixels contain only a first the predetermined chemical species; (g) repeating the previous step for each of the predetermined chemical species; (h) in each of the image frames, identifying which of the pixels contain more than one of the predetermined chemical species; (i) for each pixel that contains more than one of the predetermined chemical species, separating the contribution of each predetermined chemical species; and (j) composing separate spectral images of each of the predetermined chemical species in the sample. Also disclosed are apparati for performing these methods, comprising: (a) an illumination source for illuminating the sample with a first plurality of photons to form a second plurality of photons; (b) an optical device for receiving and directing the second plurality of photons to an imaging device; (c) an imaging device for forming a plurality of images of the sample; and (d) a processor in communication with the imaging device.

The invention provides a satellite remote sensing estimation method for surface soil moisture capable of removing vegetation cover influence. The method comprises the following steps: (1) preparing materials and data; (2) auxiliary parameter calculation (calculation of surface albedo and vegetation coverage); (3) resolving bare soil albedo from the surface albedo; (4) sensing estimation of soil moisture and drafting; (5) evaluating the accuracy of the estimation method. According to the method disclosed by the invention, the soil moisture is calculated by directly using the bare soil albedo, the remote sensing physical significance is clear, and essential intension of the soil moisture subjected to remote sensing estimation is prominent; the defect in the traditional method (a method basedon the surface albedo, such as, Peihao, et. al, 1999) that intermediate parameters need to be calculated and measured is overcome, propagation of errors among the parameters is avoided, any excessiveintermediate link does not exist, and the operation is simple and feasible; regional condition constraint that has to be owned by the traditional method (such as an optical vegetation coverage method) is broken. According to the method, the surface soil moisture in any large region can be reliably and stably estimated at high accuracy.

A far-field optical microscope capable of reaching nanometer-scale resolution using the in-plane image magnification by surface plasmon polaritons is presented. The microscope utilizes a microscopy technique based on the optical properties of a metal-dielectric interface that may, in principle, provide extremely large values of the effective refractive index n_eff up to 10²-10³ as seen by the surface plasmons. Thus, the theoretical diffraction limit on resolution becomes λ/2n_eff, and falls into the nanometer-scale range. The experimental realization of the microscope has demonstrated the optical resolution better than 50 nm for 502 nm illumination wavelength.

A vital tissue discrimination device, which includes infrared spectrum acquiring section (1, 2, 3, 4, 5, 6, 8, 9, 10, 12, 13 and 14) for acquiring infrared spectrum information from a vital tissue and an operating section (11) for discriminating normal from abnormal of the vital tissue based on the infrared spectrum information obtained by the infrared spectrum acquiring section, wherein the operating section (11) calculates a micro-cycle fluctuation component of the infrared spectrum information and discriminates normal from abnormal of the vital tissue based on the micro-cycle fluctuation component of the infrared spectrum information.

The invention discloses a material identification method and device based on laser speckle and modal fusion, and the method comprises the following steps: carrying out the data collection of a measured object through a structured light camera of a projection laser speckle structure, and obtaining a color modal image, a depth modal image and an infrared modal image; preprocessing the color modal image, the depth modal image and the infrared modal image; inputting the preprocessed color modal image, depth modal image and infrared modal image into a preset depth neural network; training an acquired data set, learning material-level features from corresponding speckle structures and color and depth modal coupling relationships, and generating an object material classification model for material classification, so as to generate a material prediction result through the object material classification model in a test stage. According to the method, material identification can be realized by utilizing interaction of laser speckles and materials and modal fusion of the laser speckles and visible light vision, and the method is simple and easy to realize.

The invention provides a super-resolution Bessel micro-imaging device and method based on multi-focus light illumination. The method comprises a laser light source, a beam-expanding collimating and reflecting component, a Gaussian fluorescence generation component which excites a sample surface to generate a Gaussian-distributed fluorescence signal according to an introduced illumination mode of equal interval switching, a Bessel fluorescence generation component which converts the Gaussian-distributed fluorescence signal into a Bessel-distributed fluorescence signal and obtains image data, and a control terminal which performs image reconstruction on image data to obtain a super-resolution sample two-dimensional information image. According to the invention, a sample is simultaneously excited through multiple focus points, the imaging range of the microscopic imaging device is improved, the sample collection time is reduced, the Gaussian-distributed fluorescence signal is converted into the Bessel-distributed fluorescence signal, the image data of the collected Bessel-distributed fluorescence signal is subjected to image reconstruction, and the super-resolution imaging at a largeworking distance can be achieved while the high signal-to-noise ratio is improved.

The invention relates to the technical field of remote sensing image information extraction, and especially relates to a county-scale crop yield estimation method based on CNN-LSTM. The method comprises the following steps: S1, acquiring and processing data; S2, superposing and filtering the data; S3, acquiring county-scale feature tensor data; S4, constructing and training a CNN-LSTM model; S5, using the CNN-LSTM model trained in S4 to estimate yield of target crops. According to the method, based on the remote sensing data reflecting the crop growth state and the environmental data influencing the crop growth, more features of county crops are extracted through a histogram statistics method and converted into tensors, so that the extracted CNN-LSTM model is trained, and the small-scale crop yield estimation precision is effectively improved.

The invention discloses a compact micro snapshot channel modulation full polarization imaging detection device and method. The detection device comprises an object lens, a full polarization modulation module and a surface array detector which are sequentially arranged along incident light, wherein the full polarization modulation module comprises a first birefringence prism, a first half-wave plate, a second birefringence prism, a second half-wave plate, a third birefringence prism, a third half-wave plate, a fourth birefringence prism and a linear polarizer which are sequentially arranged along the incident light, the parts cling to each other, the linear polarizer is arranged clinging to a photosurface of the surface array detector, and the photosurface of the surface array detector is perpendicular to an optical axis of the detection device and is at the image plane position of the object lens. The detection device is advantaged in that the full polarization modulation module capable of realizing combination prism light splitting is employed, the interference intensity information of a detected two-dimensional target through channel modulation at the certain time can be acquired through shooting an image, and two-dimensional space polarization graphs corresponding to all the Stokes polarization parameters can be acquired through utilizing a Fourier demodulation algorithm for processing.

The invention discloses a remote sensing identification method of spring corn. The method is characterized in that the spatial distribution information of the spring corn in a regional range is extracted by using the differences between the remote sensing red light reflectivity, near infrared reflectivity and normalized difference vegetation index of the spring corn and those of other surface feature types and through classification system building, training sample selection, surface feature type remote sensing attribute index time sequence curve average extraction, identification feature selection, feature threshold determining and spring corn identification model building. The method has the advantages that discrimination rules can be built by selecting multiple remote sensing attribute indexes according to prior knowledge, then decision tree classification is used to identify the spring corn in the regional range, and high identification precision is achieved; the method is high in stability and universality and applicable to the operation implementation of large-range spring corn remote sensing extraction.

The invention discloses a nadir and limb common optical path integral optical system, relates to the technical field of space optics, and aims to solve the problems that detection information is not complete, and use requirements are hard to met as a conventional spatial atmospheric remote sensing detection has single modes. A nadir and limb imager comprises a front lens group, a panorama annular lens, a relay lens group, narrow-band filters and a CCD detector. For a nadir view field, the panorama annular lens is equivalent to a thick lens; the light beam size of a light beam of the nadir view field is firstly reduced through the front lens group, and then the light beam is imaged on the CCD detector through the panorama annular lens and the relay lens group. For a limb view field, light firstly passes through the panorama annular lens to form a virtual image, and the virtual image formed by the panorama annular lens is amplified by the relay lens group and is imaged to the CCD detector. By adopting the nadir and limb common optical path integral optical system, all-direction detection of nadir 10 degrees and limb 360 degrees, and six wave bands are selected by using six narrow-band filters, so that detection information completeness and inversion accuracy of a trace gas can be improved, and the system is applicable to the field of spaceflight atmospheric remote sensing.

The invention discloses a method for researching soil organic carbon reserve change based on returning farmland to forest and returning grass. The method comprises the following steps: acquiring a previous soil type distribution diagram and a land utilization type distribution diagram of a research area; calculating the average organic carbon density of each type of soil and the organic carbon reserve of the research area based on the soil type distribution diagram and the soil type attribute recorded by the soil type of the research area; calculating the average organic carbon density of thesoil under different land utilization modes; acquiring a land utilization type distribution diagram of the research area in the latest period; based on the land utilization type distribution diagramsin different periods, the land utilization type change situation of the research area is obtained; and calculating the soil organic carbon reserve of the research area in the latest period based on the change condition of the land utilization type and the soil average organic carbon density in different land utilization modes, and evaluating the soil carbon sequestration effect of the research area after the measures of returning farmland to forests and returning grass are taken. The method can estimate and compare the soil organic carbon reserves after the land utilization changes in different periods, and improves the estimation precision.

Examples of the present disclosure relate to an apparatus and method for detecting light reflected from an object. The apparatus includes a light guiding element including a diffracting structure configured to direct incident light to an object; and an optical sensing element configured to detect light reflected from said object.

The invention provides a maize variety identification method based on deep-cascaded forest and a hyperspectral image. The method comprises the following steps: pretreating all maize image data to obtain full-waveband image data selecting the maize image data in the effective waveband; and taking the maize image data in the effective waveband as a feature set, and performing model classification byadopting a deep-cascaded forest model. The maize classification is performed by sufficiently utilizing the hyperspectral technology and the deep-cascaded forest model, compared with the ordinary machine learning algorithm, the maize variety identification method disclosed by the invention has higher identification precision.

The invention discloses a high-resolution spectral image rapid acquisition device and method. The device comprises an illumination light source, an objective lens, a spectroscope, a single-shot spectral image acquisition assembly, and a reference image acquisition assembly. The illumination light source is used for projecting illumination light onto the sample to be detected so that the sample tobe detected is amplified by the objective lens, the amplified light is divided into two parts of light by the spectroscope; one part of light enters the single-shot spectral image acquisition assemblyso as to acquire a low-resolution spectral cube of the sample to be detected, and the other part of the light enters the reference image acquisition assembly to acquire a high-resolution spectral cube. According to the invention, the high-resolution spectral image can be rapidly obtained, so that the process of applying the spectral image to medical diagnosis is accelerated.

The invention discloses a method and a device for rapidly detecting coal gangue based on a multispectral technology. According to the invention, a multispectral imaging technology is used for coal gangue detection, a coal and gangue multispectral image acquisition system is constructed, a coal gangue multispectral image is acquired, the multispectral image is processed by using an image fusion technology, and the coal and gangue multispectral image after image fusion is used for coal gangue detection. YOLO-V3 is improved, a coal gangue rapid detection model is designed, and the fused multispectral image is labeled and used for training the detection model. Finally, the trained detection model is applied to coal gangue detection. The coal gangue is detected based on the multispectral imaging technology, and compared with a visible light image, richer characteristics of the coal and the gangue can be obtained through a multispectral image, and higher accuracy is achieved. In addition, the designed improved detection model has higher detection speed, and online detection of coal gangue can be realized.

Devices and methods for determining the quality thin film materials are disclosed. The thin film materials are provided on substrates forming thin film material structures. The devices comprise a housing, a THz module with a THz source emitter and a THz detector,and a reflective base moveable relative to the THz module and configured to support the thin film material structures. The THz source emitter is configured to irradiate the thin film materials. The THz detector is configured to measure at least one reflection of the irradiation. The device is configured to calculate a parameter indicative of the quality of the thin film material based on said reflection measurements.

The invention discloses a method for determining the carbon monoxide emission flux of an environmental atmospheric pollution point source based on satellite remote sensing. On the basis of spatial and temporal distribution of carbon monoxide atmosphere observed by satellite remote sensing, smoke plumes emitted by a point source are identified and quantified by adopting a section integrated flux algorithm according to wind field information. According to the method, the carbon monoxide emission flux of an industrial source and the uncertainty and the long-time change rule of the carbon monoxide emission flux are calculated by using a section integrated flux algorithm. The transmission scale, the spatial distribution rule and the space-time evolution characteristics of the carbon monoxide emission of an industrial source can be obtained by combining atmospheric circulation, meteorological elements, topography and landform and source area pollution characteristics. Compared with a traditional emission flux quantification method, the section integrated flux algorithm based on satellite remote sensing can realize high-precision calculation of the emission flux of a point source in any region, and has important significance in the field of accurate prevention and control of atmospheric pollution.

The invention provides a soil water and evaporation ratio coupling simulation and mutual conversion method. The boundary of a temperature-vegetation index characteristic space is optimized, the soil water and the evaporation ratio share one set of parameters, and continuous retrieval of the model boundary is achieved, a soil water and evaporation ratio actual measurement data driving mode is adopted, an optimal parameter obtained by a soil water target function calibrated by a soil water actual measurement value is used to estimate the evaporation, and vice versa. The aim is to indicate that the optimal parameter obtained by calibrate the soil water actual measurement value or an optimal parameter obtained by calibrating the evaporation ratio actual measurement value can be used to estimate the evaporation ratio or the soil water without bias. The target functions for estimating the two parameters share the same set of optimal parameters. The technology can be used to realize couplingsimulation and mutual conversion of the soil water and evaporation ratio.