64 results about "False color" patented technology

The invention discloses a photovoltaic power station defect detection method based on thermal imaging data, and relates to the technical field of artificial intelligence, and the method comprises the steps: S1, collecting the thermal imaging data of a photovoltaic module under different working conditions, and carrying out the preprocessing of the thermal imaging data, and obtaining a thermal imaging data set; s2, based on the thermal imaging data set, dynamically dividing a temperature interval and calculating an adaptive bandwidth, and performing weight distribution and color band center weighted fusion by using a Sigmoid function to generate an adaptive pseudo-color image capable of enhancing local contrast; s3, constructing a double-branch defect detection model based on the original temperature data and the pseudo-color image; and S4, performing defect detection on the real-time thermal imaging data based on the double-branch defect detection model to obtain a defect detection result of the current photovoltaic power station. The method can be effectively applied to large-scale inspection operation and maintenance of the photovoltaic power station.

The invention aims to provide an RGBG type display panel sub-pixel rendering method and system based on edge judgment. The method comprises the following steps: acquiring an RGB image to be rendered; rGB pixel information of the RGB image is converted into RG pixel information or BG pixel information; the pixel with the missing sub-pixel information and the adjacent pixel share the missing pixel information. According to the invention, when the RGB data of the source image is converted into the RGBG panel display data, the condition of edge blurring or heavy pseudo color caused by the weighted average calculation of adjacent sub-pixels in the prior art can be overcome.

The present invention discloses a real-time super-resolution reconstruction method and system based on historical feature fusion. The method includes constructing a network model; constructing the network model includes: extracting linear features of the current frame to obtain a linear feature map of the current frame; extracting non-linear features and performing feature fusion on the current frame and historical frames to obtain a non-linear feature map after feature fusion; wherein, the historical frames are the first N frames before the current frame, and N is a natural number; the extraction of non-linear features of the historical frames is based on the images after motion compensation of the historical frames; based on the non-linear feature map after feature fusion and the linear feature map of the current frame, a super-resolution reconstructed image of the current frame is obtained. The present invention solves a series of problems existing in current super-resolution technologies, such as poor real-time performance, detail temporal breakage, false colors, poor generality, etc., and takes into account both real-time performance and image quality.

The present invention relates to a method for 3-D reconstruction of a leaked gas cloud based on a dual FTIR telemetry scanning imaging system, comprising the following steps: Step A: Select a monitoring area where gas leakage occurs, deploy two FTIR telemetry scanning imaging systems at different azimuths in the monitoring area, and obtain the GPS positions of each system; Step B: During the normal monitoring process, each system measures the 2-D projection column concentration image of the gas cloud and the pointing information of each pixel, such as azimuth and elevation angle; Step C: Use a geometric method to locate the cross-monitoring area and stratify it by elevation angle to obtain the monitoring area information divided by a three-dimensional grid; Step D: Calculate the path length coefficient sparse matrix of each layer, and use the simultaneous algebraic reconstruction technique (SART) to reconstruct the gas cloud distribution of each layer; Step E: Combine the gas cloud distributions of each layer into a 3-D gas cloud, calculate the center position of the gas cloud by the concentration weighting method, and display it through a false color combined with a 3-D map.

The application provides a RAW domain non-local mean image denoising method, comprising the following steps: S1, collecting a RAW image by a sensor; S2, dividing the image into N channels, such as R, Gr, Gb and B channels according to an actual Bayer format; S3, performing non-local mean filtering on each channel; further comprising: S301, calculating the similarity between each channel pixel point and the center pixel point of a neighborhood window; S302, calculating the weight according to the similarity information; S303, calculating the filtering result of each pixel point in each channel according to the weight; S4, merging the results of each channel after filtering into a RAW image, and outputting the result. The application utilizes the original characteristics of noise to perform image filtering in the RAW domain, reduces the difficulty of noise suppression, and has smaller side effects under the premise of achieving the same filtering effect; the non-local mean filtering is adopted, so that the problems of pattern noise after filtering, and false color and color cast caused by unbalanced channel filtering results are avoided.

The application discloses a kind of self-adapting edge enhancement neural network remote sensing image fish pond extraction method, comprising the following steps: selecting sentinel satellite multispectral band synthetic false color image;Fish pond area annotation dataset is constructed;Establish self-adapting edge enhancement neural network architecture, the architecture fuses the edge detection module of learnable threshold and semantic feature extraction;Integrating edge perception double attention module and pyramid pooling module, enhance multiscale feature representation ability;Multi-level deep supervision and prediction fusion strategy are used to optimize training process;Finally, fish pond area is extracted by training model and generates standardized result.The application significantly improves fish pond boundary segmentation precision, enhances the adaptability to different scale fish ponds, especially improves the detection rate of small scale fish ponds, and accelerates the model convergence process through deep supervision strategy, effectively reduces the misclassification of similar water bodies such as rivers, ditches and the like, solves the technical problems of existing technology, such as edge blur, poor multiscale adaptability, complex background interference sensitivity and high small scale fish pond detection rate.

This invention provides an image reconstruction method, an image sensor, and a terminal device. The method includes: acquiring a color filter array image collected by the image sensor; acquiring a high-frequency image and a low-frequency image based on the color filter array image; for each pixel in the high-frequency image, acquiring the region feature fusion weight and distance feature fusion weight corresponding to that pixel; for each pixel in the high-frequency image, acquiring the mixing weight corresponding to that pixel based on the region feature fusion weight and distance feature fusion weight; and fusing the high-frequency image and the low-frequency image based on the mixing weight corresponding to each pixel in the high-frequency image to generate a reconstructed image. This invention can improve the image quality noise and false colors in the edge areas while ensuring the clarity of details in the central region of the image, thereby significantly improving the overall image reconstruction quality.

The present application relates to the field of endoscope imaging, in particular to a single-channel filtering demosaicing method and system for endoscope images; the horizontal direction local gradient intensity and the vertical direction local gradient intensity of green pixels in a color filter array image are calculated, the green pixels are adaptively interpolated according to the difference between the horizontal direction local gradient intensity and the vertical direction local gradient intensity, and an initial green channel is obtained; the pixels in the initial green channel are subjected to bilateral filtering, and a filtered green channel is obtained; based on the filtered green channel, residual interpolation is used to respectively reconstruct a red channel and a blue channel, and a demosaiced image is obtained; the present application reduces the risk of false color and noise amplification, has the characteristics of strong edge preservation ability, high overall color restoration precision, simple algorithm and easy hardware implementation.

The invention discloses an image defogging method combining dark channel statistics and polarization degree constraint. The method is suitable for image enhancement and visibility improvement in a complex smog scene. According to the method, images of five wave bands in different polarization states in the same scene are collected through a polarization camera, Stokes parameters are calculated to obtain polarization degree and polarization angle information, and then atmospheric scattered light and object reflected light are distinguished. When the atmospheric light is estimated, the interference of a bright object is effectively avoided by combining the brightness and the polarization degree of a single-channel grey-scale map; in transmissivity estimation, a self-adaptive fusion strategy is provided, dark channel statistical characteristics and a polarization physical model are combined, and transmissivity estimation weight is adjusted in a self-adaptive mode according to regional polarization degree difference. And finally, realizing image restoration based on an atmospheric scattering model, and remarkably improving the information content and visual recognition effect of the defogged image by combining a multispectral false color fusion technology. Through organic combination of polarization defogging and multispectral enhancement, a complete technical scheme from image quality recovery to information depth extraction is formed, clear and information-rich image data can still be provided under severe weather conditions, and the method has important practical application value.

To generate realistic overlay images (1) which are true-color with respect to at least one false color FF(x,y) used to visualize a spectral image (3a, 3b), a method and an associated image recording device (5) are provided, which enable undesired color shifts of such a false color to be avoided in the overlay image and a high image brightness of a white light image illustrated as an image background and the original image contrast of the white light image to be substantially maintained in the overlay image in spite of the overlay. Here, at least one color channel value of the white light image, which is complementary to the respective false color to be locally displayed, is locally deliberately reduced in each case, so the higher the resulting intensity I(x,y) of the spectral image (3a) also to be visualized in the overlay image is at this point (x,y).

The invention proposes a method and an associated image recording device (5) for generating a realistic superimposed image (1) which is true in terms of at least one false color FF (x, y) for visualizing a spectral image (3a, 3b), which method and image recording device enable the avoidance of an undesired color shift of such false color in the superimposed image (1), and despite the superimposition, the white light image (2) shown as the image background in the superimposed image (1) remains substantially high image brightness and the white light image (2) remains substantially the original image contrast. For this purpose, according to the invention, at least one color channel value of the white-light image (2), which color channel is complementary to the false color to be presented in each case locally, is reduced in each case locally in a targeted manner, and the intensity I (x, y) of the spectral image (3a) to be visualized also in the superimposed image is reduced as the intensity I (x, y) is higher at this point (x, y).

The present disclosure relates to methods and systems, software programs for visualizing weak fluorescence in surgery. The method comprises: emitting excitation light (12) from an excitation light source (6) to an operating area (10) containing a weak fluorescent light source (16), and emitting white light from a white light source to the operating area (10); capturing one or more fluorescence images and one or more white light images of the operating area (10) at the wavelength range of the fluorescence (14) emitted by the weak fluorescence source (16); performing image processing on the captured image by creating a virtual region of interest (20) in the white light image and / or the fluorescent image wherein the fluorescent image outside the region of interest (20) is cut out; creating one or more false color fluorescence images visible within the visible spectrum from the one or more fluorescence images; and creating one or more composite images (50) by superimposing the one or more false color fluorescence images on the one or more white light images.

The application discloses a kind of sandstone core spontaneous imbibition experimental methods based on NMR scanning, comprising: using nuclear magnetic resonance scanning device scans to obtain the gray scale of sandstone core sample in initial state when not absorbing water vertically axial stratification and parallel axial direction;Using nuclear magnetic resonance scanning device scans to obtain the gray scale of sandstone core sample vertically axial stratification imaging and parallel axial direction and T2 curve under different spontaneous imbibition time under different time corresponding moment when soaking in spontaneous imbibition device;DCM data of the imaging result obtained is adjusted to window width window position, the color scale of all gray scale is adjusted to obtain the best false color map, and the hydrogen signal intensity of sandstone core sample along axial direction different position and parallel axial direction is analyzed to obtain fluid migration and occurrence state in sample space at different time in complete process of spontaneous imbibition.The application can be not destroyed core sample as premise, and space positioning is carried out by analyzing a large number of profile image data, and then movable water migration speed and reached position in spontaneous imbibition process are predicted.

The present application relates to an image processing method, apparatus, electronic device, and computer-readable storage medium. The method comprises: obtaining a first field of view image captured by a first camera and a second field of view image captured by a second camera, wherein the field of view corresponding to the first camera is different from the field of view corresponding to the second camera; performing global correction processing on the second field of view image based on the first field of view image to obtain a globally corrected image; the global correction includes at least one of brightness correction and color correction; performing local correction processing on the globally corrected image based on the first field of view image to obtain an intermediate image, wherein the local correction includes position correction; and fusing the intermediate image and the globally corrected image to obtain a target image. This method can reduce false colors in images and avoid image color distortion.

Computer-aided method for creating an article-based purity definition of pre-concentrates from sorting plants for solid waste materials, the method comprising the following process steps: a) Acquisition of at least two-dimensionally resolved sensor raw data regarding at least one pre-concentrate using a sensor; b1) Classification of the sensor raw data based on predefined material classes; b2) Creation of an initial false-color image based on the classification of the sensor raw data, c) Correction of the false colors of the first false color image of article sub-components; d) Creation of a second false color image based on the change in the false color of the article component regions; e) Creation of a false color distribution based on the second false color image.

The embodiment of the specification discloses a kind of dynamic pseudo-color rendering methods, equipment and medium of large image data, it is related to image rendering technical field, for solving the problem of low reading efficiency and low rendering precision of current large image data.Method includes: obtaining the source image data generated by semiconductor optical detection;Based on the resolution level corresponding to different scaling ratio, pyramid segmentation is carried out to source image data, and mixed tile data and its corresponding level row column index are constructed;Mixed tile data includes: raster base map tile data and vector overlay tile data;According to the scaling level and display area coordinates of current view, the corresponding level row column index is determined to load the corresponding target tile data;Target tile data is input into pre-training mapping model, and the corresponding pseudo-color mapping value generated by the pre-training mapping model is obtained, to be rendered and displayed based on pseudo-color mapping value.

This application provides an image processing method, apparatus, and electronic device, relating to the field of image processing technology. These methods can more effectively suppress false color and restore more high-frequency details during image depigmentation, denoising, and super-resolution processing, thereby improving image quality. The image processing method includes: acquiring an RGBW image from an image sensor, the RGBW image including a red channel, a green channel, a blue channel, and a white channel; inputting the RGBW image into a convolutional neural network model to obtain an RGB image output by the convolutional neural network model, the convolutional neural network model including a cascaded feature extraction module, a reconstruction module, and an upsampling module, the feature extraction module and the reconstruction module being used for the depigmentation and denoising processes, and the upsampling module being used for the super-resolution processing process. The RGB image includes a red channel, a green channel, and a blue channel, and the resolution of the RGB image is greater than that of the RGBW image.

The application relates to a security X-ray image augmentation method, system, device and medium. The method estimates high-energy data and low-energy data of a contraband false color image inserted into a background false color image through a bottom-layer physical model of a security inspection machine, inserts the contraband false color image into a specified target area of the background false color image, then completes mapping of the high-energy data and the low-energy data to the false color image, generates a false color image with specific contraband inserted at a specified position, realizes TIP data enhancement based on the high-energy data and the low-energy data, can quickly generate a large amount of training data with labeled information, and achieves the purposes of directional data amplification and data enhancement.

The invention discloses a device identification and maximum temperature calculation method based on an infrared thermal imaging pseudo-color image. The method comprises the following steps: acquiring the infrared thermal imaging pseudo-color image comprising target equipment, a color gradation scale and a maximum / minimum temperature display area; identifying a target device from the image and extracting an image area of the target device; according to the pre-calibrated position, the highest temperature value, the lowest temperature value and the color gradation scale region image are extracted respectively, and the pixel height is calculated; positioning a highest-temperature pixel point in the equipment area and acquiring a color value of the highest-temperature pixel point; performing color matching on the color value and the color gradation scale image, determining the position of the color value on the color gradation, and calculating the height of a matched pixel; finally, according to the temperature range, the color gradation height and the matching height, the highest temperature of the equipment is obtained through proportional conversion, and the equipment name and the temperature result are output. According to the invention, equipment identification and highest temperature measurement and calculation can be automatically and accurately completed from a single infrared thermal image, and the automation level and accuracy of industrial temperature monitoring are improved.

A method for visualization of faint fluorescence in surgery. The method including: emitting excitation light from an excitation light source onto an operation area containing a faint fluorescence source and white light from a white light source, capturing one or more fluorescence images of the operation area at a wavelength range of fluorescence light emitted by the faint fluorescence source and one or more white light images, performing image processing on the captured images by creating a virtual region of interest in the white light image and / or the fluorescence image, wherein the fluorescence image is cut off outside the region of interest, creating one or more false color fluorescence images visible in the visible light spectrum from the one or more fluoresecence images, and creating one or more composite images by overlaying the one or more false color fluorescence images over the one or more white light images.

The invention belongs to the field of target tracking, and discloses a hyperspectral video-oriented small target tracking method, which comprises the following steps of: respectively calculating contribution degree scores of hyperspectral frames with consistent waveband information and all wavebands of an initial target template; forming a plurality of false color hyperspectral images and a plurality of false color initial target images; distortion is carried out to obtain a distorted hyperspectral image and a distorted initial target image, and a region of interest is obtained; features of the distorted hyperspectral image and the distorted initial target image are extracted respectively and fused to obtain a feature map, then regression is carried out in a region of interest in the feature map by using a prediction head to obtain a rectangular frame where a small target is located, and if the rectangular frame where the small target is located is not obtained in the region of interest, the small target is located; if yes, performing global search on the hyperspectral frame to obtain a rectangular frame where the small target is located, namely a tracking result of the small target; according to the invention, through band recombination and template updating, the problems that small target features are difficult to extract and are seriously influenced by shielding and other scenes are solved.

The invention relates to an image processing method and a storage medium, and relates to the technical field of image processing, and the method comprises the steps: carrying out the preprocessing of an original first image, and obtaining a second image with noise; the second image is input into an image processing model of a U-shaped network structure for convolution processing, an image set is obtained, the image set comprises a third image, and the third image and the second image are the same in size; performing denoising and demosaicing processing on the second image and the third image to obtain a target image; the problems of low image definition, noise residue, false color and false image and the like in the existing image denoising and demosaicing method are solved.

A method for determining an image quality verification (IQV) metric for false color artifacts in chromatic areas of digital images includes receiving a digital image that includes flat pure color patches and mixed color texture patches; processing the digital image in an image signal processing chain such that a red / green / blue image is produced; transforming the red / green / blue image into an LAB color space image; calculating, for each mixed color pixel in a mixed color texture patch, a chromatic distance in the LAB color space from the mixed color pixel in the mixed color texture patch to a center of each flat pure color patch; performing directional adjustments on each of the chromatic distances; and defining, for each mixed color patch, the IQV metric for the for the mixed color patch as a function of the distance metrics of each mixed color texture pixel in the mixed color patch.

The invention relates to the technical field of defect identification of image analysis, in particular to a chip packaging process defect rapid detection method and system.The method comprises the steps that hyperspectral scanning is conducted on a chip packaging area to be detected to collect a three-dimensional hyperspectral data cube, and the hyperspectral data cube after radiometric calibration is obtained through radiometric calibration processing; the method comprises the following steps: screening out a characteristic wave band combination with remarkable spectral response difference between a transparent adhesive material and a chip packaging substrate, constructing a characteristic wave band sub-data set, generating a pseudo-color image after dimension reduction mapping processing, and extracting a connected pixel set of an adhesive overflow region; calculating a physical area corresponding to the connected pixel set and a spatial position coordinate of the connected pixel set in the chip packaging area; if the physical area exceeds a preset glue overflow area threshold value, judging that the chip packaging process has a glue overflow defect and outputting a corresponding spatial position coordinate; and the detection accuracy of the transparent excessive glue defect in the chip packaging process is effectively improved.

The present invention relates to the field of image processing technology, and more particularly to an image processing method, electronic device, readable medium, and program product. The method corrects the pixel values ​​of abnormal pixels (hereinafter referred to as pixels to be corrected) among edge pixels in Remosaic Raw using the pixel values ​​of non-abnormal, same-color pixels adjacent to the pixels (i.e., correction pixels). In this way, the pixels to be corrected after Remosaic processing of the raw image data output by a 2×2 OCL sensor can be corrected while preserving the image's details and texture and ensuring the clarity of the output image, thereby resolving the problem of false colors or black edges in images obtained based on the image data processed after Remosaic.

Systems for endoscopic visualization with advanced overlay image frames including color image data and multispectral or fluorescence image data. A system includes an image sensor comprising a pixel array that detects electromagnetic radiation and reads out a plurality of data frames. The system includes an image sensor processor that receives the plurality of data frames read out by the image sensor, wherein the plurality of data frames comprises a plurality of color data frames and a plurality of advanced data frames. The image signal processor renders a video stream comprising a plurality of advanced overlay data frames, wherein each of the plurality of advanced overlay data frames comprises a color data frame and a false color overlay generated based on an advanced data frame. The image signal processor executes an adaptive persistence algorithm to stabilize movement of the false color overlay across the plurality of advanced overlay data frames.

The application discloses a forest fire situation analysis method and device based on satellite remote sensing and a medium, and belongs to the technical field of remote sensing application. The method comprises the following steps: collecting multispectral satellite remote sensing image data of a region to be researched, and preprocessing the multispectral satellite remote sensing image data to obtain a multispectral satellite orthographic image data set; in the case that a fire occurs in the region to be researched, performing false color band synthesis on the multispectral satellite orthographic image data set to obtain a false color image, and extracting a burned pixel from the false color image to determine a forest fire line contour; calculating an area in the forest fire line contour based on Arcgis software, and calculating a difference value of a vegetation normalized index before and after a disaster based on ENVI software to evaluate a fire intensity. The application realizes the identification of a forest fire through an efficient and accurate method, and timely risk evaluation after the occurrence of the fire.

The invention discloses an improved NDWI-based multi-source remote sensing image coastline extraction method and a related device, and relates to the technical field of coastline identification, and the method comprises the steps: carrying out the first preprocessing of an optical remote sensing image, obtaining a false color remote sensing image, carrying out the second preprocessing of a synthetic aperture radar remote sensing image, and obtaining a false color remote sensing image; obtaining a preprocessed synthetic aperture radar remote sensing image; performing fusion processing on the false color remote sensing image and the preprocessed synthetic aperture radar remote sensing image to obtain a fused image; on the basis of a two-stage adaptive Gaussian weighted NDWI method, the fused image is calculated, and a normalized difference water body index graph after Gaussian weighting is obtained; performing sea-land segmentation on the normalized difference water body index graph after Gaussian weighting by using a clustering algorithm to obtain a sea-land separation binary graph; and performing morphological processing and coastline vector extraction on the sea-land separation binary image to obtain coastline data of the vector. According to the method, the coastline extraction precision and reliability can be improved.

To provide a method of, a system for, electronic equipment for, and a storage medium for detecting forest land disturbance as a better service by efficient, precise and reliable forest land resource monitoring, environment protection, and ecological protection restoration supervision management through forest land disturbance detection based on a full polarization SAR image.SOLUTION: A method of detecting forest land disturbance based on a full polarization SAR image has the steps of acquiring a full polarization SAR image in a target region, segmenting the image into that of a reference time phase and that of a monitoring time phase, subjecting the segmented full polarization SAR image to pre-processing including a polarization matrix conversion of the SAR image, Refined Lee filtering, and false color synthesis, acquiring a false color synthesis SAR image, inputting the false color synthesis SAR image into an optimized ground surface change detection model to extract a ground surface change patch, combining the patch with a radar vegetation index RVI image to acquire an initial forest land disturbance patch, carrying out overlapping check for the initial forest land disturbance patch to acquire a forest land disturbance patch in the target region, and generating a visualized result.SELECTED DRAWING: Figure 1

The present disclosure relates to methods and systems, software programs for visualizing weak fluorescence in surgery. The method comprises the following steps: emitting excitation light (12) from an excitation light source (6) to an operating area (10) containing a weak fluorescent light source (16) and emitting white light from a white light source to the operating area (10); capturing one or more fluorescence images and one or more white light images of the operating area (10) at the wavelength range of fluorescence emitted by the weak fluorescence source (16); performing image processing on the one or more fluorescence images and creating one or more false color fluorescence images from the one or more fluorescence images wherein the contrast between the fluorescence emitted by the weak fluorescence source (16) and the background is increased; and creating one or more composite images (50) by superimposing the one or more false color fluorescence images on the one or more white light images.