239 results about "Pixel brightness" patented technology

The invention provides an aluminum film sealing defect real-time detection method and system based on multi-algorithm fusion, and relates to the technical field of intelligent manufacturing, and the method comprises the steps: triggering an industrial camera at a detection station to collect an original image of a pesticide aluminum film sealing on a conveyor belt; performing adaptive equalization operation on the original image through pixel brightness distribution data, eliminating light fluctuation and surface reflection interference, and outputting a standardized image; three types of defect detection are synchronously executed based on the standardized image, a dynamic threshold segmentation algorithm is combined with local area brightness analysis to detect edge damage, a contour extraction algorithm is adopted to calculate bottleneck center offset to recognize seal offset, wrinkle defects are recognized based on a surface texture feature analysis algorithm, and a primary detection result is output. The aluminum film sealing defect detection method is based on multi-algorithm fusion, has strong anti-interference capability, real-time detection performance and data traceability, and provides an efficient and reliable automatic solution for aluminum film sealing quality management and control.

The invention relates to the technical field of display screen defect detection, and discloses a mobile phone display screen defect detection method, device and equipment and a storage medium, and the method comprises the steps: collecting display images of a to-be-detected mobile phone display screen at a plurality of observation angles; the reflection intensity distribution of the display image is analyzed by using polarization optical characteristics, and a de-reflection image is generated after surface reflection components are separated; transforming the pixel brightness of each observation angle in the de-reflection image to a unified reference viewpoint to obtain a unified reference viewpoint image, and extracting a first defect feature vector of each pixel in the unified reference viewpoint image; and fusing the first defect feature vectors extracted from multiple observation angles to obtain a second defect feature vector, comparing the second defect feature vector with a preset threshold, and outputting a defect detection report. According to the application, multi-angle information advantages are utilized, and a defect classification mechanism based on RGB channel response differences is established; and various defect types of bright spots, dark spots, color cast and line defects can be accurately distinguished.

The invention relates to the technical field of automatic control, in particular to a detection equipment attitude real-time correction system which comprises an attitude trajectory extraction module, a trajectory stability evaluation module, an interference area recognition module, a light spot trajectory reconstruction module and an attitude correction control module. According to the invention, through comprehensive extraction of the direction change trend, the angle difference and the trajectory overlapping condition in the light spot image sequence, the trajectory trend of the attitude change between continuous frames is established, so that the identification of the attitude offset evolution process is more detailed, the attitude change stability analysis is realized in the time sequence dimension, and the accuracy of the attitude change is improved. Interference area identification is carried out by means of luminance continuity and spatial distribution consistency of light-emitting pixels, real light spots and lagging residual signals can be effectively distinguished, a light spot track path is reconstructed on the basis of interference removal, and real-time calculation of a track dynamic offset direction and an angle change amplitude is combined with track correction rule setting, so that the accuracy of track correction is improved. And the specific correction action matching of the deviation state is realized.

The invention relates to the field of image processing, in particular to an industrial feeding anomaly recognition method based on visual flow detection, and the method comprises the steps: obtaining an image sequence for optical flow calculation through the collection and preprocessing of an image sequence of an industrial feeding port; performing nonlinear fusion on the pixel brightness value and the time brightness change rate to obtain a highlight suppression factor; carrying out distribution analysis on the local gradient structure tensor characteristic value to obtain a gradient structure confidence factor; performing joint weighting on the highlight suppression factor and the gradient structure confidence factor to obtain a dynamic space-time confidence weight; weighted optical flow calculation and variance threshold judgment are carried out on the dynamic space-time confidence coefficient weight, a feeding abnormal state recognition result is obtained, and therefore the problems of optical flow calculation distortion and abnormal misinformation caused by mirror surface highlight in the SMT micro component feeding process are solved.

The invention discloses a textile color difference detection method based on image data, and relates to the technical field of image processing and computer vision, and the method comprises the following steps: S1, collecting an image of a textile with a high reflection characteristic under a standard light source, constructing a light intensity prediction model, and carrying out the analysis based on pixel brightness distribution, identifying a brightness abrupt change region and a saturation critical region, and generating an image-level saturation risk probability graph; s2, performing multi-scale exposure area division on the image based on the image-level saturation risk probability graph, setting a target brightness range of each exposure control sub-area, and recording a global exposure parameter of the image acquisition equipment as an initial baseline of exposure scheduling; according to the method, pixel-level brightness convergence is realized through light intensity prediction and area exposure control, real color distribution is reconstructed in combination with color compensation, and a closed-loop process is constructed by introducing model self-correction, so that the detection precision and consistency of the micro chromatic aberration of the high-reflective fabric are improved, and the automation and industrial applicability are enhanced.

The invention relates to the technical field of image enhancement, in particular to a dark field detail dynamic enhancement method and system for an LED backlight source, and the method comprises the following steps: setting a brightness threshold T1 and a brightness threshold T2 according to the brightness component of an input image frame, the dynamic backlight range of the associated LED backlight source and a gamma curve; according to the method, the pixel brightness is subjected to fine-grained division through partition judgment of the brightness component of the input image frame, so that more accurate dark field area positioning is realized, and the local linear transformation coefficient is constructed for the dark field mask area by using the original brightness component, so that the subsequent enhancement operation has continuity and edge retention characteristics; and adaptive classification of the image content is realized through a structure complexity threshold value, then differential enhancement strategies such as multi-direction texture enhancement, normal direction sharpening and curved surface smoothing are extracted respectively, and gain distribution conforming to different region characteristics is established, so that the dark field detail identification granularity is higher.

The invention provides a low-gray-scale image imaging defect visual detection method and system for an OLED display screen. The method comprises the following steps: aiming at original image data of a display screen, extracting a gray scale picture with a pixel brightness mean value lower than a preset brightness threshold value as a first image, carrying out color characteristic analysis on the first image, and generating a second image marked with a chromaticity feature vector; identifying the chromaticity feature vector according to the second image, generating a feature vector matrix for representing chromaticity distribution of each pixel in the second image, and performing color jump analysis through the feature vector matrix to obtain a third image; extracting a jump region in the third image, and setting marks for distinguishing different dispersion distribution for chromaticity distribution dispersion distribution according to the jump region to obtain a fourth image; and identifying dispersion distribution according to the fourth image, combining with a chromaticity abnormal pixel region in the hopping region, performing pixel classification in the hopping region, and setting defect marks for pixels with imaging defects represented by a classification result to obtain a fifth image.

Systems, apparatus, and methods for post-processing video e.g. frame denoising. Noise reduction techniques may be employed to improve the quality of digital video. Frames may be extracted from a video. Synthetic frames may be created using motion data between the extracted frames. Synthetic frames may be masked to exclude pixels from the composite frame. Thresholds used in masking may vary based on the temporal distance of the extracted frame used to create the synthetic frame and the extracted frame. Masking may be based on frame differences between extracted and synthetic frames (e.g., sub-pixel / luminance differences), areas of lower quality motion data (e.g., occlusions), or edge detection in the extracted frames. Synthetic and extracted frames may be composited generating frames having less noise. The composited frame may be based on averaging pixel values across the synthetic and extracted frames. Composited frames may be compiled and encoded into denoised video.

The invention relates to the technical field of AMOLED display driving, and discloses an AMOLED display driving chip integrated system with high refresh rate and low power consumption. The system comprises a pixel flow time sequence analysis module, a dynamic compensation model construction module, a refresh rate adaptive modulation module and a power consumption constraint optimization module. A pixel stream time sequence analysis module captures video source frame cache data in real time, and extracts a pixel brightness distribution matrix and an inter-frame change gradient; a dynamic compensation model building module builds a dynamic voltage compensation network according to the current frame and historical frame information, and fuses the current frame and historical frame information through a space-time attention mechanism; the refresh rate adaptive modulation module generates a decision diagram according to the inter-frame change gradient, and regulates the refresh rate in different regions; and the power consumption constraint optimization module is combined with a chip junction temperature parameter to generate a partition backlight current constraint coefficient matrix. The system can optimize display image quality and fluency, realizes power consumption fine control, guarantees stable operation of a chip, and is suitable for various AMOLED display terminals.

The invention relates to the field of image recognition, discloses an image recognition method and an image recognition system, and systematically solves the core pain point of traditional document recognition through optical-topology fusion processing and a dynamic resource allocation mechanism. The image recognition method is composed of an acquisition module, a grid module, a phase module, a setting module and a distribution module, pixel brightness is calculated and coded based on document RGB data, and a two-dimensional coding matrix is generated; constructing a geometric correction grid, forming a nonlinear constraint field, and enhancing the anti-deformation capability of the image; generating spiral phase light waves in the constraint field by using a spatial light modulator, and generating a time-varying phase map; determining a local topology index by detecting the number of phase jump times; and extracting the closed boundary region as a character block, and generating an analysis result file. The system breaks through traditional limitation, improves image geometric correction precision, feature extraction sensitivity and boundary judgment accuracy, efficiently completes document analysis, and is suitable for scenes such as document digitization and information retrieval.

The invention discloses an image fusion enhancement method for a multi-signal-source liquid crystal splicing screen, and relates to the technical field of large-screen display control, and the method comprises the steps: building a virtual coordinate system taking a physical gap as a reference at an input end, carrying out the decoding, time synchronization and unified mapping of a multi-source heterogeneous signal, converting the multi-source heterogeneous signal into a unified color space, and carrying out the image fusion enhancement of the multi-signal-source liquid crystal splicing screen. The display consistency of different signal sources is ensured; then, a compensation model based on a brightness attenuation function is introduced into the splicing boundary area, edge pixel brightness is subjected to self-adaptive correction, and brightness unevenness caused by physical gaps is relieved; calculating the content complexity based on the row-level gradient magnitude in the fusion screen area, dynamically constructing a content-sensitive fusion weight, and carrying out weighted fusion on the images on the two sides to generate a transition image frame; and through joint output of the transition image frame and the original side image frame, visual seamless connection of the splicing gap area is realized. Therefore, the integral continuity and visual experience of tiled display are effectively improved while the image detail fidelity is ensured.

This application relates to image processing and provides a method and electronic device. The method includes: capturing a to-be-displayed image; detecting a display operation on the image; obtaining brightness channel data in response; acquiring a pixel brightness value based on the channel data; determining a target brightness value based on a current screen brightness and a first brightness value; selecting a first or second gain coefficient according to the pixel brightness value to process the pixel and generate a processed image; and adjusting the display screen to the target brightness value to display the processed image. This solution avoids image brightness distortion and expands the dynamic range, making the displayed image more vivid and closer to actual scenarios.

The invention relates to the technical field of cigarette package detection, in particular to an intelligent identification method and system based on cigarette package image analysis, and the method comprises the steps: obtaining the corner coordinates of an icon, extracting longitudinal and transverse offset parameters, judging the arrangement stability, constructing a structure chart, and analyzing the inter-column offset fluctuation and interval abnormal marking combination area. And identifying a connection path in the hopping direction of the sealing edge, judging a dislocation and hopping overlapping area, extracting the remaining boundary, and measuring and calculating the angle and distance classification connection sequence between the centers of the graph. According to the method, an icon corner arrangement structure is constructed, transverse and longitudinal offset differences are fused, a dislocation judgment basis is established, pattern dislocation sections are identified according to an offset accumulation value and sequence grouping, an edge sealing path is formed by combining pixel brightness change and a jumping direction, intersection fragments are screened to remove abnormal areas, center points are extracted, and classification connection is performed according to the offset direction. And analyzing the label arrangement path.

The invention discloses an unmanned aerial vehicle camera exposure adjusting method and device, and relates to the technical field of image processing. Acquiring a real-time image and real-time illumination intensity shot by a camera of the unmanned aerial vehicle; calculating the pixel brightness value of the real-time image to obtain a brightness standard deviation; calculating the real-time illumination intensity to obtain an illumination intensity ratio; when the brightness standard deviation is greater than a brightness threshold value or the illumination intensity ratio is greater than an illumination threshold value, determining that the current shooting environment of the unmanned aerial vehicle is a strong light source, calling a first exposure adjustment strategy, and adjusting exposure parameters of the camera of the unmanned aerial vehicle based on the first exposure adjustment strategy; and when the brightness standard deviation is smaller than or equal to the brightness threshold value and the illumination intensity ratio is smaller than or equal to the illumination threshold value, determining that the current shooting environment of the unmanned aerial vehicle is a non-strong light source, calling a second exposure adjustment strategy, and adjusting the exposure parameter of the camera of the unmanned aerial vehicle based on the second exposure adjustment strategy. By implementing the provided technical scheme, the overall quality of the image is improved.

The embodiment of the invention provides an image processing method, electronic equipment, a storage medium and a program product. The image processing method comprises the following steps: determining the original pixel brightness of a current image according to image data to be processed; dividing the original pixel brightness into a plurality of data branches; obtaining a histogram corresponding to the original pixel brightness of each data branch; determining a tone mapping curve of each data branch based on a tone mapping model and the histogram; fusing the tone mapping curve of each data branch to obtain a fusion curve; obtaining target pixel brightness corresponding to the original pixel brightness based on the fusion curve; and determining target image data corresponding to the to-be-processed image data based on the original pixel brightness and the target pixel brightness. According to the scheme of the embodiment, automatic tone mapping is realized, and the flexibility and the adaptability of tone mapping are improved.

The invention discloses a bill identifier identification method, which comprises the following steps: continuously acquiring a plurality of exposure images of a target bill at different exposure times through acquisition equipment, and fusing the plurality of exposure images according to the pixel brightness of a plurality of image pixels in the exposure images to obtain a target exposure image corresponding to the target bill; performing image enhancement on the target exposure image to obtain a target enhanced image, determining target boundary information of the region of interest according to the target enhanced image and a boundary detection model, and determining a target mask region corresponding to the region of interest according to the target boundary information; the method comprises the steps of obtaining a gradient magnitude of each pixel in a target mask region, dividing the target mask region into a plurality of pixel regions, determining a dynamic threshold value of each pixel region according to the gradient magnitudes of the plurality of pixels in each pixel region, and generating a target image according to the plurality of dynamic threshold values, the bill identification of the target bill is determined based on the target image through the pre-trained image identification model, and the bill identification precision can be improved.

The invention discloses a lens smudginess monitoring method, computer equipment and a storage medium, and relates to the technical field of image processing, and the method comprises the steps: controlling an image collection device to shoot a plurality of images with different exposure degrees, and forming an image sequence from overexposure to underexposure; processing the image sequence, and respectively extracting a smudginess feature based on pixel brightness variance, a smudginess feature based on block brightness gradient change and a smudginess feature based on frequency domain enhancement; and fusing the extracted multiple smudginess features to generate smudginess area information. By collecting a multi-exposure image sequence and respectively extracting pixel brightness variance, block brightness gradient change and frequency domain enhancement features, light transmission abnormity, local response abnormity and edge texture features of a dirty area in exposure change are effectively captured, multi-dimensional features are fused, the accuracy, sensitivity and robustness of recognition of various pollutants are improved, and the recognition accuracy, sensitivity and robustness of various pollutants are improved. The problem of misjudgment of single-frame detection in a complex environment is solved, and reliable and comprehensive monitoring of lens smudginess is realized.

The invention relates to the technical field of image recognition, in particular to a printed circuit board defect detection method and system based on image recognition. The method comprises the following steps: collecting a multi-angle board image of a printed circuit board to be detected, and determining a highlight saturation region according to gray gradient information in the multi-angle board image; weighting and correcting the pixel value of the highlight saturation region by using the pixel brightness information of the neighborhood of the highlight saturation region, and generating an image to be analyzed; identifying silk-screen character information in the to-be-analyzed image, and generating a character bounding box according to the silk-screen character information; combining the gray distribution information and the edge direction information in each character bounding box to reconstruct a character coverage texture, and generating a to-be-detected image; and according to a preset circuit board defect library, matching defect features in the to-be-detected image, and generating a defect detection report according to a matching result. According to the invention, the detection efficiency is obviously improved, and the method is suitable for the production detection requirements of high-density and high-precision PCBs.

The invention discloses an AI linkage data system based on Internet of Things multi-source data fusion, and relates to the technical field of image recognition, and the system comprises a collection module which is used for collecting a real-time image of a fire, and selecting a suspected region with the brightness higher than a brightness threshold value in the real-time image; the preprocessing module is used for performing Gaussian filtering preprocessing on the suspected area; the method comprises the following steps: denoising a suspected region by dynamically adjusting Gaussian filtering parameters, calculating a brightness change rate of pixels on the inner and outer sides of an edge to obtain a gradient band width, dividing suspected region sub-blocks, extracting sub-block texture feature vectors by adopting a local binary pattern algorithm, and calculating a region overall texture entropy value by combining a region texture similarity matrix to obtain a region texture similarity matrix; the difference between the strong reflection light spots and real flames can be accurately recognized, the AI chip is prevented from misjudging the strong reflection light spots as newly added fire behaviors, then the linkage control module is prevented from mistakenly starting a spraying system in a non-fire behavior area, and damage of a large number of materials due to water stains caused by mistaken spraying is reduced.

For meeting the future demand of high quality yet economically feasible high dynamic range video program creation, the inventor proposes a method of in a video camera (201) setting a video camera capturing mode of specifying output pixel luminances in one or more graded versions of output video sequences of images, comprising: —an operator of the video camera moving to at least two positions (Pos1, Pos2) in a scene which have a different illumination compared to each other, and capturing at least one high dynamic range image (o_ImHDR) for each of those at least two positions of the scene; —a color composition director analyzing for each of the at least two positions the captured at least one high dynamic range image to determine a region of maximum brightness, and determining at least one of an iris setting, a shutter time, and an analog gain setting for the camera; —capturing for each position of one of the at least two positions (Pos1, Pos2) a respective master capturing (RW) using the at least one of an iris setting, a shutter time setting, and an analog gain setting for the camera, and keeping iris, shutter time and analog gain settings constant for later capturing in at least the corresponding position; —determining at least a respective first graded image (ODR) for the respective master capturing, which consists of mapping by a respective luminance allocation function (FL_M) of digital numbers of the master capturing to nit values of the first graded image (ODR), by the color composition director establishing a shape of such luminance allocation function; and —storing the respective luminance allocation functions (Fs1, Fs2) for the at least two positions, or parameters uniquely defining these functions, in respective memory locations (221, 222) of the camera.

The invention discloses a three-dimensional cultural relic 3D scanning ultra-high-definition enhancement method, device and equipment and a medium, and relates to the technical field of three-dimensional modeling, and the method comprises the steps: obtaining a light supplement enhancement image set, carrying out the dense matching strategy of the light supplement enhancement image set, and generating image pairs with consistent structures; minimum coverage rectangular region extraction is carried out on the image pairs with the consistent structures, and redundant complementation region pairs are generated; performing texture completion processing on the receptor region image in the redundant completion region pair to obtain a texture completion image set; and key image pairs are extracted based on the final texture completion image set, a matching point pair set is obtained through scale invariant feature transformation, and a matching point three-dimensional coordinate set is obtained through triangulation of each matching point pair. According to the invention, pixel-by-pixel brightness compensation and color equalization are carried out by combining the time-weighted exposure consistency index, so that illumination equalization adjustment of the region with uneven local exposure is realized.

The invention discloses a target state parameter determination method and device, a storage medium and an electronic device, and relates to the technical field of smart home, and the target state parameter determination method comprises the steps: obtaining a target face video stream of a target object outputted by an image collection module, obtaining a light supplementing state signal output after the light supplementing module supplements light to the space where the target object is located; determining a light supplement condition corresponding to each frame of image in the target face video stream according to the light supplement state signal, and determining a reference light intensity offset of a forehead area and a nose root area in each frame of image according to the light supplement condition corresponding to each frame of image; and according to the reference light intensity offset of the forehead region and the nose root region in each frame of image, pixel-by-pixel correction is performed on the pixel brightness value of each frame of image to obtain a corrected video stream, and a target state parameter of the target object is determined according to the corrected video. By adopting the technical scheme, the problem that the state parameters of the target object cannot be accurately determined is solved.

The invention provides a photographing method and electronic equipment. The photographing method comprises the following steps: acquiring a pre-flash image of a target scene when a flash lamp is in a pre-flash stage; the pre-flashing image is segmented into a first pixel set and a second pixel set, the first pixel set meets a first condition, the second pixel set meets a second condition, the first condition represents that the flash lamp has a first influence degree on the pixel brightness of the first pixel set, and the second condition represents that the flash lamp has a second influence degree on the pixel brightness of the second pixel set; the second condition indicates that the flash lamp has a second influence degree on the pixel brightness of the second pixel set, and the first influence degree is greater than the second influence degree; and according to the first pixel set and the second pixel set, determining a current value when the flash lamp is in the main flash stage, so as to obtain an image when the target scene is in the main flash stage.

An image processing apparatus comprises a receiver (401) receiving an image comprising first pixel brightnesses encoded in accordance with a perceptually uniform Electrical to Optical Transfer Function, EOTF. A converter converts this to second pixel brightnesses encoded in accordance with an EOTF representing a logarithmic mapping from optical light values to the second pixel brightnesses and an image processor circuit (411) applies a brightness adjustment processing to the second pixel brightnesses. The converter (410) comprises a first converter (601, 605) generating intermediate pixel brightnesses applying a logarithm function to the first pixel brightnesses A second converter (603) generates intermediate pixel brightnesses by applying a second logarithm function to an output value of the perceptually uniform EOTF for the first pixel brightness divided by a divisor equal to the first pixel brightnesses raised to a power of an exponent having a value exceeding 1. A combiner generates the second pixel brightnesses by combining the intermediate pixel brightnesses.

The present application relates to the technical field of image understanding, in particular to a page element semantic analysis method based on visual language enhancement; a dense optical flow field and inter-frame state transition rule joint analysis is performed on an acquired visual image frame sequence, a two-dimensional spatial region in which a local rendering state is abnormal is identified, and a space-time feature matrix is constructed; a space-time feature matrix and an edge pixel brightness attenuation gradient and a visual darkening feature matrix of a neighborhood environment are extracted, and a pseudo-depth blocking parameter is identified; foreground multi-modal features inside the space-time feature matrix and background multi-modal features of an external environment are extracted, and a relative entropy divergence in a multi-modal semantic space is calculated; a multi-dimensional joint determination model is constructed using the pseudo-depth blocking parameter and the relative entropy divergence, and whether the spatial region is an interference pop-up window is identified; when the identification result is an interference pop-up window, warning data containing attribute information of the interference pop-up window is output, and an adaptive locking mechanism of interface analysis state is triggered.

A grayscale compensating method, a displaying driving method, an apparatus, a system, a chip and a medium. The grayscale compensating method includes: determining compensation coefficients corresponding to sub-pixels in a display panel, wherein the compensation coefficients are for characterizing compensation modes and compensation magnitudes of brightness compensations to the sub-pixels, wherein the compensation modes include a mode of increasing a brightness and a mode of reducing a brightness; and based on the compensation coefficients, compensating for the to-be-displayed grayscale values of the plurality of sub-pixels, to reduce a difference in emitted-light brightnesses of the plurality of sub-pixels. The display panel includes a first displaying region block and a second displaying region block, the compensation coefficients corresponding to the sub-pixels within the first displaying region block are greater than 0, and the compensation coefficients corresponding to the sub-pixels within the second displaying region block are less than 0.

The present application relates to a method for driving a display panel and a display device, wherein the method includes: a timing controller detecting the current display mode; when the display mode is a variable refresh rate mode, the timing controller detecting the refresh frequency of the image; when the timing controller detects a change in the refresh frequency of the previous frame, the timing controller calls a pixel brightness correction table and a gamma voltage table corresponding to the refresh frequency of the previous frame at the beginning of the current frame; and a microcontroller driving the display panel to display the image using the pixel brightness correction table and gamma voltage called by the current frame when displaying the next frame. This application solves the problem in the prior art of a long delay in calling the corresponding pixel brightness correction table after the refresh frequency is switched, resulting in noticeable flickering in the switching image.

Provided is a display module, including a display panel and a timing controller. The brightness adjustment module in the timing controller is connected to the light strip control module, and the light strip control module in the timing controller is connected to the light strip; the brightness adjustment module is configured to adjust brightness of pixels of a first video frame to be played to acquire a second video frame and a total pixel brightness of the second video frame; the brightness adjustment module is further configured to drive the display panel to display the second video frame and send the total pixel brightness to the light strip control module; and the light strip control module is configured to control an emission color and brightness of the light strip based on color information and the total pixel brightness.

The present disclosure relates to glare mitigation using image contrast analysis for autonomous systems and applications. In various examples, a contrast value corresponding to pixels of one or more images generated using one or more sensors of a vehicle can be computed to detect and identify objects that trigger glare mitigation operations. A pixel luminance value is determined and used to compute a contrast value based on comparing the pixel luminance value to a reference luminance value based on a set of pixels and corresponding luminance values. A contrast threshold can be applied to the computed contrast value to identify glare in the image data, thereby triggering a glare mitigation operation so that the vehicle can modify a configuration of one or more illumination sources to reduce the glare experienced by occupants and / or sensors of the vehicle.

The invention relates to the technical field of intelligent driving, and discloses a lane changing control method for automatic driving, which comprises the following steps: obtaining a visual image of the surrounding environment of a vehicle; dividing the visual image into a plurality of brightness layers according to the pixel brightness values, and respectively executing image processing operations corresponding to the pixel brightness values on different brightness layers to obtain a plurality of enhanced visual images; respectively inputting the plurality of enhanced visual images into a target detection model, and identifying whether a barrier vehicle exists on the side of the vehicle; and generating a lane changing control instruction according to the identification result, and controlling the vehicle to execute lane changing operation according to the lane changing strategy. According to the invention, the recognition accuracy of the obstacle vehicle can be improved, so that the accuracy of the automatic driving chip for controlling the vehicle to perform lane changing operation is improved.