50 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 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.

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.

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.

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.

Method for live display of digital color images on a monitor (4), in particular in false color display, - wherein the color images are captured with an image sensor (2) of an endoscopic image acquisition system (1) in a color image acquisition mode (15) and are transmitted to the monitor (4) as image signals (8) in order to be displayed live on the monitor (4), and - wherein, for this purpose, an image processing unit (3) arranged in a camera control unit (9) of the image acquisition system (1) generates the respective image signals (8) from the color images in color image acquisition mode (15), which are supplied to an image signal input (5) of the monitor (4) in order to reproduce the color images live on the monitor (4), characterized in that - that the camera control unit (9) retrieves information relevant for image reproduction from the monitor (4) before the actual live display of the color images on the monitor (4), - that the retrieved information is used by the image processing unit (3) to adapt the generated image signals (8) before these image signals (8) are transmitted to the monitor (4), - wherein the information retrieved by the monitor (4) includes a color characteristic of the monitor (4) and - wherein a calculation unit (11) of the camera control unit (9) calculates at least one color compensation parameter (20) from this and the image processing unit (3) uses this color compensation parameter (20) to color-correct the image signals (8) generated in the color image acquisition mode (15).

The application provides an endoscope imaging method and system, an imaging method and device, and an electronic device. The system comprises: a white light illumination module for obtaining standard white light to illuminate a target tissue of an endoscope; a beam splitting module for splitting reflected light of the white light into a first light beam and a second light beam; a white light imaging processing module for obtaining a standard white light image using the first light beam; simultaneously, a hyperspectral imaging processing module for collecting a hyperspectral image using the second light beam, and selecting two or more narrowband images with a center wavelength difference reaching a preset difference from a plurality of narrowband images of the hyperspectral image; and, based on at least any two narrowband images of the two or more narrowband images, promoting and inhibiting mechanism fusion and color channel combination are performed to generate a false color image; and an image display module for displaying the standard white light image, the hyperspectral image, and the false color image, so as to realize real-time examination of the endoscope.

The present application relates to the technical field of pedestrian detection, and particularly relates to an infrared image pedestrian detection method, comprising the following steps: S1: combining YOLOv5 with an attention module and Unet to form a YOLO-Unet network; S2: the attention module and the Unet form an attention Unet, the attention Unet selects an infrared image or a pair of visible light and infrared pedestrian images, the attention Unet encodes and decodes the selected infrared image or the pair of visible light and infrared pedestrian images, generates a false color image and transmits the false color image to the YOLOv5; S3: the YOLOv5 utilizes a DIoU-NMS technology to perform post-processing and a detection loss function, and performs feature extraction and pedestrian classification. The YOLO-Unet network can improve the performance of thermal image pedestrian detection without the need for a complex detection model or a large data set.

The invention discloses a cerebral blood flow diffusion assessment method based on attention guidance sparse image fusion, and belongs to the technical field of medical image processing, and the method comprises the steps: collecting an original data set of a CTA image sequence of an ischemic smoke disease, constructing a plurality of groups of sparse image pairs each comprising a diffusion image and a blood vessel image, and obtaining an image training set; constructing a sparse image fusion and visualization model; training a sparse image fusion and visualization model by using the image training set to obtain a trained sparse image fusion and visualization model; and processing a to-be-detected ischemic smoke disease CTA image by using the trained sparse image fusion and visualization model to obtain a corresponding reconstructed fusion image, and completing evaluation based on a pseudo-color image of the corresponding reconstructed fusion image and a visualization result. The problems that an existing method still has limitation in the aspect of sparse image fusion precision, cross-modal feature extraction and fusion efficiency is insufficient, and the accuracy of an evaluation result is limited are solved.

The present application relates to a kind of color image edge false color elimination method, comprising the following steps: step 1, determine design parameter, and the image to be corrected is converted to HSV space, obtain H, S, V each channel image;Step 2, carry out gray scale corrosion operation to saturation S channel, and the image after corrosion and saturation difference graph;Step 3, saturation difference graph carries out threshold segmentation, obtains saturation correction area;Step 4, minimum intensity graph is extracted from the image to be corrected;Step 5, intensity correction area is extracted from minimum intensity graph;Step 6, false color correction area is determined from intensity correction area and saturation correction area, and false color correction is carried out.The false color elimination method provided by the present application can slow down / remove the false color generated when color image is shot "black and white" high contrast edge, improve color image edge quality, be conducive to subsequent image processing, also more in line with eye viewing intuition.

Method for reproducing digital color images on a monitor (4) in false color representation, - wherein the color images are captured using an image sensor (2) of an endoscopic image acquisition system (1) in a color image acquisition mode (15), - wherein an image processing unit (3) of the image acquisition system (1), which is arranged in a camera control unit (9) mediating between an endoscope (10) of the image acquisition system (1) and the monitor (4), generates respective image signals (8) from the recorded color images, which are supplied to an image signal input (5) of the monitor (4) in order to reproduce the color images live on the monitor (4) in false color representation, - and wherein the image processing unit (3) calculates a respective false color representation of the color images, based on image data recorded with the image sensor (2) and on the basis of at least one stored false color which is assigned to a specific image area, characterized in that - that before the actual reproduction of the color images on the monitor (4) a digital color test image (6) is displayed on the monitor (4) which has at least one stored false color that is used for the false color display, - that a digital image (7) of the color test image (6) displayed on the monitor (4) is captured by means of the image sensor (2) and compared with the original color test image (6), - that, depending on a determined deviation between the image (7) and the original digital color test image (6), at least one color compensation parameter (20) is determined and - that subsequently, in the color image capture mode (15), at least one color compensation parameter (20) is used to adjust the image signals (8) generated in the color image capture mode (15) before these image signals (8) are transmitted to the monitor (4), - so that the image signals (8) are color-adapted to the monitor (4) used, and thus a color-accurate reproduction of the at least one false color stored on the monitor (4) can be achieved.

This invention discloses a controllable pixel displacement-driven joint demosaicing and super-resolution reconstruction method, comprising: 1. Constructing an original image sequence acquisition system consisting of a piezoelectric displacement module, a control module, and an image acquisition module, acquiring multiple frames of original image sequences through controllable sub-pixel displacement; 2. Constructing a joint demosaicing and super-resolution reconstruction network based on the multiple frame sequences, performing feature extraction and fusion on the multiple frame sequences; 3. Introducing a direction-aware wavelet enhancement module into the network, enhancing edge texture expression through wavelet decomposition, sub-band directional modulation, and reconstruction; 4. Introducing a structure-aware convolutional kernel attention module into the network, adaptively adjusting the convolutional kernel response according to local structural complexity to suppress false colors and structural distortion. This invention utilizes known displacement information to improve the determinism of original image sequence fusion and the detail fidelity and color consistency in high-frequency regions, and is applicable to scenarios such as industrial camera visual inspection and precision measurement.