44 results about "Blue band" patented technology

The invention discloses a generalized vegetation coverage-based product fusion method, system and device, and a storage medium. The method comprises the steps of obtaining a satellite remote sensing image with a near-infrared band, a red band, a green band and a blue band; calculating a characteristic ratio index according to the near-infrared band, the red band, the green band and the blue band; constructing a linear transformation function according to the characteristic ratio index; setting a virtual minimum value vmin = kxmin of the characteristic ratio index; according to the linear transformation function and the virtual minimum value, constructing a generalized vegetation coverage-based power function; setting vmin + = vmin + rho; determining the characteristic power of the generalized vegetation coverage-based power function according to the condition that the generalized vegetation coverage-based power function value corresponding to the vmin + is equal to the vmin +; according to the principle of product enhancement, the red wave band and the green wave band are respectively enhanced by utilizing a generalized vegetation coverage-based power function with determined characteristic power. The standardization degree of the product enhancement processing process and the consistency of the processing result are improved.

A condenser lens (21) comprises a first surface (211) and a second surface (212). Light including components of the red band, the green band, and the blue band is incident on the first surface (211). The incident light including the components of the red band, green band, and blue band is emitted from the second surface (212). An aspherical convex lens section (213) is formed in the center of the second surface (212). An aspherical concave lens section (214) is formed around the convex lens section (213).

The invention discloses a method for detecting miRNA-21 based on a paper base-friction power generation sensing chip of intelligent DNA hydrogel and application. The method comprises the following steps: preparing Pt-Ni NPs; the preparation method comprises the following steps: preparing hydrogel embedded with Pt-Ni NPs; designing a paper-based micro-fluidic chip; the miRNA-21 is recognized through a CRISPR-Cas12a system, the gel is cut, internal Pt-Ni NPs signal molecules are released, and a blue strip is displayed on the paper-based micro-fluidic chip; a nano generator is connected with the chip to prepare a paper base-friction power generation sensing chip; along with the change of the concentration of the miRNA-21, the gel releases Pt-Ni NPs with different concentrations to cause the voltage change on the paper-based friction power generation sensing chip, and the change value is in direct proportion to the concentration of the miRNA-21. The chip is used for detecting miRNA-21 and has the advantages of simplicity in operation, small size, portability, high sensitivity, good specificity and short detection period.

The invention discloses a water and soil conservation steep slope remote sensing supervision pattern spot interpretation method and system, and relates to the technical field of high-resolution satellite image processing, and the method comprises the following steps: S1, carrying out the multi-scale segmentation of a remote sensing image, and determining an optimal segmentation scale; s2, based on the brightness, the normalized vegetation index, the blue band mean value, the near-infrared band mean value, the ratio residential area index, the boundary index and the shape index, establishing a bare area extraction algorithm, and using the bare area extraction algorithm to remove interference ground objects in the remote sensing image segmented in the S1 to obtain a suspected disturbance pattern spot image; s3, DEM data are collected and preprocessed, gradient calculation is conducted through the preprocessed DEM data, and a gradient base map is obtained; and S4, performing image overlay analysis on the slope base map and the suspected disturbance pattern spots, and extracting the steep slope naked map spots in the target range. According to the method, the reclamation pattern spots in the gradient range can be extracted according to the reclamation prohibition range standards of steep slopes in different regions, and the extraction precision is remarkably improved.

The invention relates to the field of remote sensing mapping, and discloses a farmland protection forest extraction method based on an anthocyanin reflection vegetation index of an enhanced near-infrared and blue wave band, and the method comprises the steps: 1, obtaining images, and splicing the obtained images through employing a tool of embedding to a new grid in ArcGIS software; step 2, calculating a vegetation index, and providing RMARI-NIR and RMARI-RGB indexes suitable for different scenes; 3, making a farmland protection forest label data set; and step 4, uploading a label data set and a research area vector range on a Google Earth Engine platform, dividing a training set and test set proportion, calculating a Kappa coefficient and total precision as evaluation indexes, using the evaluation indexes as a verification method of innovation feasibility, carrying out farmland protection forest identification training classification through a random forest (RF) model and additionally fusing a characteristic wave band and an index wave band, and carrying out farmland protection forest identification training classification. The classification result and the field boundary range are overlapped, mask operation is applied to extract and obtain the distribution position information of the farmland protection forests, the spectral characteristics of the farmland protection forests are highlighted according to the extraction requirements, the distinguishing degree between the farmland protection forests and other ground objects is enhanced, and the method is suitable for generalization in various environments.

The invention discloses a generalized vegetation coverage-based superposition fusion method, system and device, and a storage medium. The method comprises the steps of obtaining a satellite remote sensing image with a near-infrared band, a red band, a green band and a blue band; performing inter-spectrum fusion on the near-infrared band and one or more of the red band, the green band and the blue band, taking the fused band combination as a numerator, taking the corresponding band combination before fusion as a denominator, and calculating a characteristic ratio index; constructing a linear transformation function according to the characteristic ratio index; setting a virtual minimum value vmin = kxmin of the characteristic ratio index; according to the linear transformation function and the virtual minimum value, constructing a generalized vegetation coverage-based power function; determining the characteristic power of the generalized vegetation coverage-based power function according to the condition that the generalized vegetation coverage-based power function value corresponding to the characteristic threshold value of the characteristic ratio index is equal to epsilon; and according to a superposition enhancement principle, respectively enhancing a red wave band and a green wave band by utilizing a power function which determines a characteristic power and is based on generalized vegetation coverage. According to the invention, the standardization degree of the enhanced processing process and the consistency of the processing result are improved.

The present disclosure provides a Group II-VI core-shell quantum dot and a preparation method therefor. A quantum dot shell having a gradient alloy structure is gradually grown by using a precursor that has a reactivity gradient. The gradient alloy structure has a band gap that gradually increases from inside to outside, thereby solving the problem of difficulty in epitaxial growth caused by a decrease in the surface activity of a quantum dot along with an increase in the size thereof. By using zinc halide and octanethiol to regulate crystal facets, the proportion of polar facets on the surface of the quantum dot is increased, and the stability of the quantum dot is significantly improved. Moreover, provided is a low-cadmium quantum dot core. A hot-injection method is used to perform nucleation and growth of ZnSe at a high temperature, a cadmium precursor is then added after the stable nucleation of ZnSe, and cadmium / zinc ion exchange is performed by utilizing the binding energy of selenium / cadmium that is stronger than that of selenium / zinc, thereby forming a CdZnSe ternary core, which can solve the problem of it being difficult for blue-light quantum dots that use CdZnSe as a light-emitting core to cover the pure blue band.

The invention discloses a duckweed type eutrophication water body monitoring method based on sentinel No.2 satellite images, and relates to the technical field of water body monitoring, and the method comprises the following steps: carrying out atmospheric correction processing on sentinel No.2 L1 C-level satellite images in a non-duckweed growth season and a duckweed growth season, and then re-sampling all wave bands to the same resolution; performing mean filtering on a blue wave band, a green wave band, a red wave band, a near-infrared wave band and a narrow near-infrared wave band of the multi-wave-band surface reflectance image after re-sampling in the non-duckweed growth season and the duckweed growth season, and then performing wave band synthesis to obtain a non-duckweed growth season wave band synthesis image and a duckweed growth season wave band synthesis image; and calculating the proportion of the duckweed growth range in the water body range by using the non-duckweed growth season waveband synthetic image and the duckweed growth season waveband synthetic image. The duckweed type eutrophication water body can be rapidly monitored in a large range at low cost.

The invention discloses a marine surveying and mapping picture data vectorization method, which comprises the following steps of: performing coarse registration and fine registration on a historical nautical chart picture to realize spatial alignment of an image and a geographic coordinate system; based on an optimal index indexing algorithm, sensitive wavebands are selected from red, green and blue wavebands and characteristic indexes, and the characteristic indexes comprise an enhanced water body index, an ultra-green index, a normalized green and blue difference index and a visible light vegetation index; performing brightness contrast enhancement, Gaussian blur, sharpening, color clustering and binarization processing on the SWB to generate an element enhanced binary image; point element extraction: adopting a Tesseract engine to train a customized model, identifying point element characters and positions in the binary image, and generating vector point data and an attribute table; and line element extraction: deleting the point elements extracted from the binary image, performing broken line connection processing on the binary image after the point elements are deleted, and generating continuous vector line elements based on the end point distance and the tangential direction.

The application discloses a kind of based on sentinel-2 satellite image's duckweed type eutrophication water monitoring method, it is related to water monitoring technical field, including the following steps: after the atmospheric correction processing of sentinel-2 L1 C level satellite image of non-duckweed growing season and duckweed growing season, all wavebands are resampled to the same resolution, after mean filtering to the blue band, green band, red band, near infrared band, narrow near infrared band of multi-band surface reflectance image after resampling of non-duckweed growing season and duckweed growing season, then band synthesis is carried out, obtain non-duckweed growing season band synthesis image and duckweed growing season band synthesis image;The proportion of duckweed growing range in water range is calculated using non-duckweed growing season band synthesis image and duckweed growing season band synthesis image.The present application can realize the fast, large-scale, low-cost duckweed type eutrophication water monitoring.

The invention provides a snow clearing and shed covering progress monitoring method, device and equipment based on Sentinel-2 images and a medium, and the method comprises the steps: obtaining multi-stage Sentinel-2 image data of snow clearing and shed covering within a preset time range, and constructing a time sequence image data set; obtaining vector basic data of the greenhouse land, and cutting the time sequence image data set based on the vector basic data to obtain target Sentinel-2 image data; constructing a greenhouse accumulated snow index based on the normalized difference snow index and the blue wave band reflectivity; according to the method, a greenhouse accumulated snow index grid map of target Sentinel-2 image data is calculated, a Fisher-Jenks algorithm is adopted to classify snow removal and greenhouse covering, and the area and proportion of classification results are counted, so that the problems that the snow removal and greenhouse covering monitoring effect is weak and measures cannot be taken in time in a greenhouse field due to the fact that accumulated snow in a complex terrain or when a snow layer is weak cannot be recognized are solved.

The application discloses an AOD inversion method and system based on multiple vegetation indexes, and the method comprises the following steps: finding a dark pixel based on multiple vegetation indexes on the basis of satellite remote sensing image data after processing; calculating the average apparent reflectivity of red and blue bands by counting the number of dark pixels in a preset range and calculating the average apparent reflectivity of red and blue bands; obtaining the surface reflectivity of red and blue bands and calculating the ratio of the two according to the observation geometry data of satellite remote sensing and a lookup table established in advance; continuing AOD inversion when the difference between the ratio and a preset ratio is greater than a preset threshold; obtaining the surface reflectivity of red and blue bands and the ratio smaller than or equal to the preset threshold requirement through multiple iterations, and calculating AOD according to the extinction coefficient of different aerosol types. The AOD inversion method and system provided by the application use the dark pixel determined by multiple vegetation indexes, realize accurate determination of the dark pixel, and further improve the accuracy of AOD inversion.

The invention belongs to the technical field of remote sensing application, and relates to a fire point identification method and system based on medium-high resolution satellite remote sensing data. The method comprises the following steps: acquiring spectral data of an ultra-blue wave band, a SWIT1 wave band and a SWIT2 wave band of a medium-high resolution satellite; calculating the reflectivity of the spectral data of the ultra-blue wave band; performing cloud removal processing to calculate the radiance values of SWIT1 wave bands and SWIT2 wave bands of all pixel points in a non-cloud area; calculating normalized short wave infrared difference indexes of all pixel points; and based on the normalized short-wave infrared difference index, performing fire point identification on the non-cloud region data by adopting a decision tree. According to the invention, early-stage small-scale fire points can be identified, and fire point rapid spreading caused by fire early-stage identification lag can be avoided to form a large-scale fire; fire point misjudgment or missed judgment caused by misjudgment of cloud layer shadows and high-reflection ground objects as suspected fire points is avoided; and in combination with the waveband characteristics of the medium-high-resolution satellites, the data advantages of the medium-high-resolution satellites are brought into full play, and the fire point identification precision is improved.

The invention relates to the technical field of visible light multi-angle radiation tea garden gap separation, in particular to an unmanned aerial vehicle visible light multi-angle radiation tea garden gap separation method, system and device suitable for a complex mountainous area and a medium, and the method comprises the steps that a tea garden true color image is obtained, data is preprocessed, and a visible light orthoimage is obtained; drawing a section sample line according to the visible light orthoimage, and extracting RGB spectrum curve graphs of each ground feature in different time periods; according to the wave band curve graphs of the ground features on the sample lines at different time periods, analyzing the wave spectrum characteristics of the three wave bands of red, green and blue of the ground features; based on an analysis result, determining characteristics and differences of red, green and blue spectrum curves of each ground feature in different time periods, and designing a separation algorithm formula; and substituting a separation algorithm into the tea garden image data for calculation, and performing threshold segmentation on a single-band image result after calculation to separate tea garden gap ground features so as to extract tea trees.

The invention discloses a beach garbage remote sensing monitoring method based on automatic double-threshold segmentation, and the method comprises the steps: generating a self-adaptive flight task planning scheme through obtaining the monitoring demand information and multi-source environment data of a target beach region, and controlling an unmanned plane platform to collect a high-resolution remote sensing image data set; after a digital orthoimage is generated through preprocessing, a green band component and a blue band component of the digital orthoimage are extracted, a green band segmentation threshold interval and a blue band segmentation threshold interval are calculated based on a local statistical feature adaptive algorithm, and a first candidate garbage distribution binary image and a second candidate garbage distribution binary image are generated through binarization segmentation processing. And obtaining beach garbage distribution vector data through space fusion and noise elimination processing, carrying out space-time change detection analysis and pollution level evaluation, and outputting a beach garbage monitoring report. Intelligent planning is realized through multi-source data fusion, the problem of spectrum overlapping is solved by adopting dual-band local adaptive threshold segmentation, and reliable technical support is provided for beach garbage treatment.

The present invention discloses a superposition fusion method, system, device and storage medium based on generalized vegetation cover, the method comprising: obtaining a satellite remote sensing image having a near-infrared band, a red band, a green band and a blue band; performing inter-spectral fusion of the near-infrared band with one or more of the red band, the green band and the blue band, calculating a characteristic ratio index using the fused band combination as a numerator and the corresponding band combination before fusion as a denominator; constructing a linear transformation function based on the characteristic ratio index; setting a virtual minimum value v of the characteristic ratio index as min =kx min A power function based on generalized vegetation cover is constructed based on the linear transformation function and the virtual minimum. The characteristic power of the power function based on generalized vegetation cover is determined by the power function value corresponding to the characteristic threshold of the characteristic ratio index being equal to ε. According to the principle of superposition enhancement, the power function based on generalized vegetation cover with the determined characteristic power is used to enhance the red and green bands, respectively. This invention improves the standardization of the enhancement process and the consistency of the processing results.

The application discloses a hyperspectral remote sensing image change detection method based on adaptive iterative filtering, and specifically comprises the following steps: step one, selecting three bands with the largest information quantity from two groups of hyperspectral remote sensing images at different times; step two, writing the selected two groups of bands into the red, green and blue bands of a natural image in the order of the index value from small to large; step three, performing adaptive region growing on the two pictures pixel by pixel, if the difference between the pixel value of the neighborhood and the center pixel is less than the standard deviation of the eight-neighborhood pixels, the pixel is merged into the adaptive region, otherwise, the pixel is not merged; step four, performing region growing on the two filtered pictures in step three again to obtain a change amplitude graph; and step five, calculating the threshold of the obtained change amplitude graph to obtain a final change detection result graph. By adopting the method, the homogenous regions on the picture are more obvious, and the precision of the hyperspectral remote sensing image change detection is improved.

The features of this protractor are as follows (1) and (2): (1) In the front view, the outer periphery of the full circle is marked clockwise with an angle scale ranging from 0° to 360°, and in order to make the 1° markings easier to see and measure, the 5° markings are made longer than the other marks every 10°, and a stepped scale is formed with the 1° markings being the shortest and the 2° markings and subsequent marks successively longer until the 10° markings are the longest. Of the stepped scales, the 2° markings, 4° markings, 6° markings, and 8° markings at each of the 10° markings are filled in with circles larger than the width of the markings to form easy-to-see circular scales. In addition, the numbers "0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 260, 270, 280, 290, 300, 310, 320, 330, 340, 350" are displayed for each 10° scale unit, with a light red band behind them to make the numbers easier to read. Furthermore, the top of each half (5°) of each 10° scale unit is filled in with a red inverted triangle to form easily identifiable inverted triangular scale marks. (2) In the rear view, the outer periphery of the full circle is marked counterclockwise with an angle scale ranging from 0° to 360°. To make the 1° markings easier to see and measure, the 5° markings are made longer than the other markings, and a stepped scale is formed in succession, with the 1° markings being the shortest and the 2° markings and subsequent marks successively longer until the 10° markings are the longest. Of the stepped scales, the 2° markings, 4° markings, 6° markings, and 8° markings in each of the 10° markings are filled in with a circle at the top, larger than the width of each marking, to form easy-to-see circular scales. In addition, the numbers "0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 260, 270, 280, 290, 300, 310, 320, 330, 340, 350" are displayed for each 10° scale unit, and a light blue band is displayed behind them to make the numbers easier to read.In addition, the top of each half (5°) scale marking for each 10° scale unit is filled in red to form an inverted triangle-shaped scale marking that is easy to identify.

The present application provides a light source device capable of improving the use efficiency of the internal space of the light source device by suppressing the increase in the number of components and a projection device provided with the light source device. The light source device is provided with: a rotating wheel device (150) having a rotating wheel (151) including a reflection region that reflects blue band light and a transmission region that transmits at least red band light and green band light; and a dichroic mirror (200) that transmits blue band light and red band light and reflects green band light, the dichroic mirror (200) including an intersection portion (200a) that is crossed in a manner overlapping a portion of the rotating wheel (151) and is irradiated with blue band light and red band light and green band light.

The fabrication process of a transparent display screen based on the triple strong directional scattering of dielectric particles includes the following steps: (1) mixing transparent substrate material and dielectric sphere particles in a mixer; (2) drying the mixed material in a drying oven to remove moisture; (3) stretching the uniformly mixed and dried material in a casting machine to ensure that the thickness of the stretched film does not exceed 0.1 mm. The mechanism of the color transparent display screen provided by this invention is the triple strong directional scattering of dielectric particles, which can simultaneously achieve high forward scattering characteristics of red, green and blue bands in simple dielectric sphere particles. Therefore, most of the light can be localized to one side of the display screen, which is significantly improved in terms of display brightness and color display compared to the reported nanostructures that only support a single LSP resonance. The thickness of the transparent display screen can be controlled below 0.1 mm, which provides a new idea and method for the fabrication of transparent display screens based on the strong directional scattering of dielectric particles and has great application prospects.

The present disclosure provides a II-VI core-shell quantum dot and a preparation method thereof. By using a precursor with a gradient change in reactivity to gradually grow a quantum dot shell with a gradient alloy structure, the gradient alloy structure has a gradually increasing band gap from the inside to the outside, solving the problem that quantum dots are difficult to be epitaxially grown due to the decrease in surface activity with the increase in size. By using zinc halide and octyl mercaptan for crystal face regulation, the proportion of the polar surface of the quantum dot surface is increased, and the stability of the quantum dot is significantly improved. Furthermore, a little-cadmium quantum dot core is provided, by using a hot injection method to perform nucleation and growth of ZnSe at a high temperature, and then adding a cadmium precursor on the basis of stable nucleation of ZnSe, using the stronger binding energy of selenium / cadmium than selenium / zinc for cadmium / zinc ion exchange, and then forming a CdZnSe ternary core, the problem that it is difficult for a blue quantum dot with a CdZnSe light-emitting core to cover a pure blue band can be solved.

The present invention discloses a product fusion method, system, device and storage medium based on generalized vegetation cover, the method comprising: obtaining a satellite remote sensing image having a near infrared band, a red band, a green band and a blue band; calculating a characteristic ratio index according to the near infrared band, the red band, the green band and the blue band; constructing a linear transformation function according to the characteristic ratio index; setting a virtual minimum value v of the characteristic ratio index to be 0. min =kx min ; According to the linear transformation function and the virtual minimum, a power function based on generalized vegetation cover is constructed; let v min+ =v min +ρ; by v min+ The corresponding power function value based on generalized vegetation cover and v min+ The power function based on generalized vegetation cover is determined to have a characteristic power; and according to the principle of product enhancement, the power function based on generalized vegetation cover with the determined characteristic power is used to enhance the red band and the green band respectively. The present invention improves the standardization of the product enhancement process and the consistency of the processing results.

The invention relates to the technical field of remote sensing image processing, in particular to a small beach shoreline accurate extraction method and system based on bare soil-water body double-index collaboration, and the method comprises the following steps: obtaining a multi-temporal Landsat surface reflectance image set which covers a target area and is subjected to radiometric calibration and wave band unified naming; obtaining a clean image set; generating a binary beach mask based on the surface reflectance of each pixel in the clean image set in a blue band, a green band, a red band, a near-infrared band and a short-wave infrared band; performing morphological closing operation on the binary beach mask to fill the fine holes to obtain a continuous mask; vectorizing and geometrically simplifying the continuous mask to obtain an initial beach face vector; and performing post-processing operation on the initial beach face vector to obtain a final beach boundary vector. According to the technical scheme, the beach can be effectively distinguished from adjacent water bodies, vegetation, buildings and other ground objects, and false lifting and missing lifting are remarkably reduced.

The present invention provides a target monitoring method and system based on drone cruising, which relates to the field of computer technology. First, the present invention obtains RGB crop images, crop spectral images, and fuselage posture data generated by the target drone during cruising. Second, based on the red, green, and blue bands in the crop spectral image, the RGB crop image is channel-enhanced to form an enhanced crop image vector. Then, the red edge band in the crop spectral image and the enhanced crop image vector are globally fused to form a global crop semantic vector. Furthermore, based on the semantic information of the fuselage posture data, the global crop semantic vector is gated and filtered to form a target crop semantic vector. Finally, crop monitoring data is analyzed based on the target crop semantic vector. Based on the above, the relatively low reliability of crop monitoring in the prior art can be improved.

The invention relates to the technical field of remote sensing images, and provides a multispectral remote sensing image tobacco vegetation index calculation method and an image optimization method, and the method comprises the following steps: inputting a multispectral remote sensing image; performing radiometric calibration and atmospheric correction on the multispectral image; acquiring reflectivity of a near-infrared wave band, a red wave band, a green wave band and a blue wave band; and calculating the tobacco vegetation index VIT based on the reflectivity of the near-infrared band, the red band, the green band and the blue band. The tobacco vegetation index VIT is suitable for a multispectral image and a hyperspectral image acquired by an unmanned aerial vehicle and a multispectral image acquired by a satellite, the tobacco vegetation is remarkably highlighted, the tobacco vegetation is remarkably distinguished from other vegetation, and the blank that the vegetation index does not aim at the tobacco plant is filled.

The invention relates to a vegetation identification method and device based on an unmanned aerial vehicle image, a readable medium and a program, and the method comprises the steps: obtaining the unmanned aerial vehicle image of a to-be-identified region, and calculating a constructed RGBSI vegetation index based on the brightness values or reflectivity of the red light wave band, the green light wave band and the blue light wave band of the image, and extracting a vegetation region from the image of which the RGBSI vegetation index is calculated by using a threshold segmentation method. The RGBSI vegetation index constructed by the method combines the strong reflection of green vegetation in a green light wave band and the absorption characteristics of the green vegetation in red and blue wave bands, when the method is used for vegetation identification, an image histogram of a vegetation index grey-scale map image calculated by RGBSI has a good double-peak form under the condition of medium and high vegetation coverage, a threshold can be rapidly determined by using a maximum entropy threshold method, and the method can be applied to vegetation identification. And the threshold value is generally close to 0. The overall extraction precision of identifying the vegetation-containing image by using the RGBSI index is more than 90%, the extraction precision is high, and the extraction effect of vegetation with medium and high vegetation coverage is better.

Light-emitting diode module, LED module, which is configured to emit white light, wherein the LED module has: a blue light-emitting diode (30) configured to emit blue light with a first peak wavelength in a range of 420 nm to 465 nm; at least one wavelength conversion material (54, 56) configured to convert part of the blue light into converted light of another wavelength; and a near-infrared wavelength conversion material (58) configured to be excited by the blue light of the blue light-emitting diode (30) to emit an additional light with a second peak wavelength in a range of 740 nm to 900 nm and a full width at half maximum (FWHM) of 120 nm or less, wherein the near-infrared wavelength conversion material (58) Ca(Al 12-x-y ,Ga y )O 19 :xCr 3+ (0≤x≤1, 0≤y≤6) exhibits, where the converted light, another part of the blue light, and the additional light combine to form the white light, and wherein a spectrum of the white light thus formed has a peak intensity in the range of 740 nm to 900 nm, and the peak intensity is greater than or equal to 4.5% of a peak intensity in a blue band from 420 nm to 465 nm.

The application provides a crop yield prediction method and system based on unmanned aerial vehicle multi-spectral image fusion, and belongs to the yield prediction field.The crop yield prediction method comprises the following steps: collecting multi-spectral images of crops in a target area before the crops are mature and determining a crop yield prediction area; extracting gray images of five bands from the crop yield prediction area; determining the texture features of each band of each gray image; determining six texture indexes according to the texture features of each band; determining six vegetation indexes according to the average reflectivity of the five bands; determining six color indexes according to the average gray values of red, green and blue bands; determining a yield index according to the six texture indexes, the six vegetation indexes and the six color indexes; and determining the crop yield of the target area by using a random forest method according to the yield index. The image processing method reduces the influence on the crops, and the texture indexes, the vegetation indexes and the color indexes are fused, so that the yield prediction accuracy is improved.

A high-color-gamut diffuser and a preparation method, relating to the technical field of diffuser materials. A high-haze diffusion layer (A), a quantum dot layer (B), and a specific spectral absorption layer (C) are subjected to in-mold three-layer co-extrusion molding to prepare a high-color-gamut diffuser. Green perovskite in the quantum dot layer (B) cooperates with a visible light absorber in the specific spectral absorption layer (C) to obtain an expected spectral emission profile, so that the high-color-gamut diffuser can absorb light at around 580 nm (yellow) in the spectrum. Overlaps between R / G (yellow) color filter absorption spectra are reduced as much as possible, so that leakage of other color emissions is prevented. The color gamut is expanded by means of an emission spectrum similar to those of QDs, and the high-color-gamut diffuser also has a certain absorption effect within the blue band portion of the spectrum, causing an overall loss in luminous intensity. Moreover, the luminance is increased, and chromaticity coordinates are low, which is suitable for KSF encapsulated strip lights. Furthermore, by means of spectrogram analysis and color gamut coverage area calculation, the DCI-P3 value and shielding performance are also improved.

The invention discloses a stable multi-energy-band perovskite composite structure and a preparation method thereof in the technical field of photoelectric materials. The stable multi-energy-band perovskite composite structure is formed by doping lanthanide ions into CsPb (XxY1-x) 3 (X, Y = Cl, Br and I) micron sheets, the double effects of phase separation and phase pinning are achieved through a one-step chemical vapor deposition method, ion migration is effectively inhibited, the stable multi-band fluorescence emission characteristic is achieved, the emission spectrum covers red, green and blue wave bands, and the stable multi-energy-band perovskite composite structure is suitable for large-scale popularization and application. The method has a wide application prospect in the field of optoelectronic equipment.