164 results about "Gamma correction" patented technology

The invention discloses an SLAM front-end optimization method based on brightness grading and gradient constraint, and relates to the technical field of computer vision and vision SLAM. In order to solve the defects that adaptive grading enhancement and parameterization control based on illumination types are lacked in the prior art, and feature point quality, spatial distribution uniformity and front-end real-time performance are difficult to consider in a high-frequency input scene, the invention provides a comprehensive brightness grading and feature optimization scheme. The method comprises the following steps: firstly, calculating the average brightness of an input image, dividing the image into a dark light type, a normal type and an overexposure type, and respectively adopting gamma correction, contrast limited adaptive histogram equalization and inversion enhancement strategies for different types to realize illumination adaptive enhancement; then screening high-quality feature points with significant local curvature changes; and updating the detection area. According to the method, the feature stability, the matching precision and the real-time performance of the SLAM front end in a complex indoor environment are remarkably improved, and the method is suitable for a self-localization and mapping system.

The invention discloses a self-adaptive low-illumination image enhancement method and device and a storage medium, which are used for stably outputting a high-quality image under various complex conditions. The method comprises the steps of generating an adaptive key parameter set through a preset mapping function based on brightness features; processing the brightness channel through a combined filtering strategy and carrying out adaptive weighted fusion to obtain an irradiation component; converting the brightness channel and the irradiation component to a logarithm domain and performing operation to obtain an initial reflection component; performing linear stretching processing on the initial reflection component to obtain an enhanced reflection component; performing nonlinear gamma correction processing on the irradiation component to obtain a corrected irradiation component; converting the enhanced reflection component back to a linear domain, and performing operation with the corrected irradiation component to obtain an enhanced brightness channel; and recombining the enhanced brightness channel with the original hue channel and saturation channel in the HSV color space, and converting back to the RGB format to obtain an enhanced image.

The invention relates to the technical field of display screen defect visual inspection, in particular to an LED display screen defect visual inspection method and system, and the method comprises the following steps: collecting an image of an LED display screen; performing gamma correction and noise suppression on the image of the LED display screen to obtain a preprocessed image; local contrast enhancement and adaptive threshold segmentation are applied to the preprocessed image, and candidate abnormal areas are identified; for the candidate abnormal region, extracting at least one dimension feature which comprises at least one of brightness, color, texture, edge gradient and spectral response; processing the at least one dimension feature based on a preset discrimination rule so as to distinguish real microdefects, optical artifacts and digital artifacts of the LED display screen; and outputting the type, the position and the confidence of the defect obtained by distinguishing. The detection accuracy and reliability are improved.

The invention provides a chromosome image enhancement method and system based on semantic guidance. The method comprises the following steps: S1, preprocessing; s2, outputting a deep-band probability graph, a grey-band probability graph and a shallow-band probability graph through a semantic segmentation network composed of a lightweight encoder and a multi-scale decoder; s3, implementing differential layered enhancement according to a band type: adopting local adaptive histogram equalization for a deep band, adopting central axis constraint bilateral filtering for a gray band, adopting dynamic threshold truncation and gamma correction for a shallow band, and performing weighted fusion for a transition region according to probability; s4, carrying out structure strengthening, wherein the structure strengthening comprises centromere local sharpening, stripe phase alignment, edge sensing super-resolution and overlapping region separation; and S5, performing quality evaluation based on the deep band integrity, the band stripe contrast uniformity, the SSIM and the noise density, and triggering adaptive re-enhancement if necessary. According to the scheme, the contrast ratio and details are remarkably improved while the stripe structure and the position relation are kept, and the method has the advantages of light weight, interpretability and cross-sample robustness and is suitable for being integrated into an automatic karyotype analysis process.

The invention discloses a low-illumination blurred image 3D scene reconstruction method based on Gaussian sputtering, and the method comprises the steps: S1, building a progressive iteration enhancement frame, and setting a middle brightness anchor point between low-light observation and target brightness; s2, generating a plurality of enhanced images based on the intermediate brightness anchor points in combination with histogram equalization and gamma correction technologies; s3, carrying out rapid deblurring processing on the enhanced image; s4, constructing a scene representation model based on 3D Gaussian sputtering, and performing explicit estimation and noise suppression in combination with a noise sensing module; s5, taking the reconstructed rendered image as the deblurring prior of the enhanced image of the next brightness level so as to execute deblurring processing operation, and performing iterative optimization until the target brightness is reached; and S6, generating a high-quality new view angle image based on the finally reconstructed 3D scene. According to the method, the rendering speed is greatly improved while the reconstruction quality is ensured, real-time three-dimensional reconstruction is realized, and the problem of noise amplification in a low-light environment is effectively solved.

The invention relates to the technical field of fan blade health monitoring, in particular to a vibration-illumination double dynamic compensation fan blade cracking early warning method and system. The method comprises the following steps: triggering and capturing a video key frame at a key angle through a rotation angle sensor, and carrying out image coarse alignment by utilizing SIFT feature matching; a corrected motion vector field is generated by combining physical parameters of the rotating speed and the angular acceleration, vibration time sequence compensation is carried out, and illumination time sequence compensation is completed through Gamma correction by taking a clear frame as a reference; an improved DeepSORT algorithm is adopted to associate crack tracks with crack mask contour similarity, evolution characteristics are extracted and fused with SCADA working condition data, an expansion rate model is established, and the remaining life is predicted; early warning grades are divided according to the service life and the expansion rate, four-dimensional operation and maintenance data are fused to output differential operation and maintenance strategies, and model parameters are optimized through feedback data. According to the invention, the accuracy and early warning reliability of crack detection in a complex environment are effectively improved.

The invention discloses a fluorescent microscopic image intelligent enhancement method and device and a readable storage medium, and belongs to the field of medical image processing. The method aims at solving the problems that multi-channel fusion of fluorescence images is difficult, pseudo-color mapping is not accurate, RGB processing is not uniform, and parameters depend on experience. The method comprises the following steps: acquiring a multi-channel image and separating; performing pseudo-color mapping and synthesis based on wavelength physical characteristics to obtain a synthesized image; obtaining R, G and B three-channel target histogram features of the standard library; carrying out R, G and B three-channel independent histogram specification on the synthesized image; by utilizing a genetic algorithm, taking similarity with a target histogram as a target, and adaptively optimizing independent Gamma parameters of three channels R, G and B; and performing independent Gamma correction by using the optimal parameter to obtain a final enhanced image. According to the method, physical accurate mapping, standardized correction and parameter self-adaption are realized, and the image quality is improved.

The invention provides a defect enhancement method and device based on image adaptive threshold segmentation. The method comprises the following steps: acquiring an original defect image of a defect in a non-marginal region; converting the original defect image into a single-channel grayscale image; extracting an edge region and a central region of the single-channel grayscale image according to a preset width and a preset proportion; calculating an edge pixel mean value according to the pixel value of the edge region, and calculating a central pixel mean value according to the pixel value of the central region; determining a defect type according to the edge pixel mean value and the center pixel mean value, and calculating a gray scale boundary value; constructing an enhancement coefficient array based on Gamma correction; performing defect enhancement on the single-channel grayscale image according to the grayscale boundary value and the enhancement coefficient array, and outputting an enhancement result image; the method can effectively improve the accuracy of defect enhancement.

The invention relates to an anchor hole recognition and positioning system and method, anchor protection equipment and a storage medium. The anchor hole recognition and positioning system comprises a visual sensor for collecting original image information within preset time, a laser radar for obtaining original point cloud information within the preset time and an image processor. The image processor comprises a first processing module and a second processing module; the first processing module processes the original image information based on an adaptive gamma correction algorithm and a defogging algorithm to obtain updated image information, and determines a two-dimensional target pixel area according to the updated image information and an anchor hole recognition model obtained by preset training; the second processing module processes the original point cloud information based on a pre-constructed first joint calibration relation between the visual sensor and the laser radar to obtain a three-dimensional target area; and then processing the three-dimensional target area to obtain an anchor hole position and an anchor hole center. The anchor hole identification precision can be improved.

Provided are an image processing device, a display device, and a control method whereby the luminance of an overlapping region in a projection image can be suppressed from decreasing non-linearly according to the position in the overlapping region by edge blending. This image processing device comprises an arithmetic circuit and a storage device, and transmits an output video signal to a display device. The arithmetic circuit performs gamma correction on a received input video signal using a first gamma characteristic and a second gamma characteristic, performs edge blending for adjusting the luminance of a predetermined region in an image according to the position in the predetermined region using the second gamma characteristic, and generates an output video signal. The second gamma characteristic is the inverse function of a third gamma characteristic of the display device. The third gamma characteristic has a gamma curve expressed by an exponential function. The predetermined region is a region in which the image displayed by the display device and another image displayed by another display device overlap.

The application relates to the technical field of image recognition, in particular to a children autism spectrum disorder stereotyped behavior recognition system based on video images. The system screens target pixel points from pixel points; determines a motion intensity index according to a trajectory point sequence of the target pixel points; converts the trajectory point sequence of the target pixel points into a motion vector sequence; determines direction similarity according to direction similarity between vectors; clusters the vectors based on the direction similarity, and identifies a target cluster; determines a motion regularity index according to the number of vectors in the target cluster and the direction similarity; determines a saliency index in combination with the motion intensity index; clusters the target pixel points based on the saliency index, and sets a region of interest; determines an enhancement weight according to the density of the target pixel points in the region and the saliency index; and determines a total enhancement demand value in combination with the gray scale and gradient features of the pixel points in the region; and reversely maps the total enhancement demand value into a gamma correction parameter, so that the accuracy of recognition is improved.

The application discloses a kind of based on multi-constraint priori's bayesian Retinex deep-sea image enhancement method, it is related to computer image processing method, the method is first by a kind of based on statistics color correction method to image color correction processing;Then according to Retinex principle, original deep-sea image is divided into illumination map and reflection map, in illumination map estimation, it is carried out smooth priori, structure priori and non-uniform illumination highlight area priori, and three kinds of priori conditions are combined into bayesian model;Through the method of gamma correction, illumination map and reflection map are handled, and finally output enhanced deep-sea image;Various evaluation standards and algorithm comparison show that the method proposed is more suitable for image enhancement work under deep-sea harsh environment, and the deep-sea image obtained by processing has better observation effect.

The invention provides an automatic Gamma correction method and device, display equipment and a storage medium, and the method comprises the steps: adjusting a register value through a dynamic adaptive step length search algorithm for a plurality of preset binding points, and enabling the current brightness of the binding points to approach the target brightness; based on the register value of the adjusted binding point and the brightness data, calculating a register value of a non-adjusted binding point by adopting a first fitting model; monotonicity check is performed on the calculated register value, the non-monotonic register value is corrected, and polynomial fitting is adopted to replace traditional linear interpolation, so that the nonlinear response characteristics of the panel can be fitted more accurately, the deviation degree of a Gamma curve is remarkably reduced, visual color gradation faults are reduced, and the performance of the panel is improved. Compared with a traditional one-by-one approximation method, the dynamic step length algorithm is accelerated by about 30%, the time consumed for single-machine adjustment on a production line is effectively shortened, a closed-loop feedback mechanism is introduced, an automatic adjustment strategy can be shown in real time according to a panel, and manual adjustment and optimization according to different IC models are not needed.

The invention provides a fan blade image adaptive parallel backlight enhancement method, and relates to the technical field of fan blade inspection, and the technical key points are that the method comprises the following steps: image preprocessing; performing color space conversion and brightness normalization on the preprocessed RGB image; constructing a gamma correction-histogram equalization double-path parallel adaptive image enhancement model; a dynamic weight coefficient is designed, and the histogram equalization image and the gamma correction image are dynamically fused; and based on the dynamic parameters, establishing a five-dimensional parameter space, and obtaining a backlight enhancement image under the optimal parameter combination by using a network search method. Through YUV space brightness channel separation and double-channel parallel enhancement, while a gamma correction branch recovers details of a dark area, a histogram equalization branch is used to suppress an overexposure area so as to realize dynamic balance of the dark area and a bright area in a backlight image; realizing collaborative optimization of global brightness balance and local detail enhancement by adopting a dynamic weight fusion strategy; and a self-adaptive optimization mechanism is realized through a grid search method.

The invention belongs to the technical field of image processing, and provides a low-illumination image enhancement method based on an HSV (hue, saturation and value) color space, which comprises homomorphic filtering preprocessing, HSV space mapping, pixel truncation linear stretching, gamma correction processing, contrast enhancement processing, saturation optimization, RGB (red, green and blue) space mapping and color balance processing. Through fusion of pixel truncation linear stretching, gamma correction processing and contrast enhancement processing, parts with extreme pixel value distribution are eliminated, the pixel values of the image in a target range are enhanced, and the brightness and contrast of the low-illumination image are improved; through saturation optimization, the naturalness of the image is kept while the color brightness is enhanced, and color distortion is avoided.

A display panel, a method for gamma correction of a display panel and a device for gamma correction of a display panel are provided according to the present disclosure. The method for gamma correction includes: determining a target grayscale interval where the to-be-displayed grayscale is located and a target sub-frame corresponding to the target grayscale interval based on a to-be-displayed grayscale; correcting a gamma of the target grayscale interval including: in each of sub-frames other than the target sub-frame, providing a grayscale interval data signal to the sub-pixel, and in the target sub-frame, providing a data signal to the sub-pixel, and correcting based on collected optical data to obtain a calibration data signal. Further, a refresh period is divided into at least two sub-frames for gamma correction, and different sub-frames correspond to different grayscale intervals.

The invention discloses an endoscope artifact segmentation method and system based on a physical model, and relates to the technical field of medical image processing, and the method comprises the steps: obtaining endoscope calibration parameters through radiation calibration and geometric calibration, and carrying out the preprocessing of a collected endoscope image, including noise suppression and gamma correction, converting the image from an RGB space to a color space matched with a physical model, and separating diffuse reflection and specular reflection components; based on a Fresnel law and a micro-surface reflection theory, establishing a physical reflection model, and deducing a local surface normal vector, a specular reflection coefficient and a diffuse reflection rate of each pixel; an initial highlight mask is obtained by constructing a mirror surface probability graph and utilizing adaptive threshold segmentation, morphological optimization is carried out, a highlight area is accurately positioned, and an artifact segmentation result is output through pixel segmentation. Therefore, by accurately modeling the relationship between the light source and the reflection, the influence of the specular highlight artifact in the endoscopic image on the image quality is effectively solved.

A liquid crystal display device comprises a liquid crystal panel and a control unit configured to drive the liquid crystal panel, wherein the liquid crystal panel includes a first substrate, a liquid crystal layer, and a second substrate, all of which are provided in a stated order, the first substrate includes a first electrode and a second electrode either stacked via a first insulating layer or disposed opposite each other, the second substrate includes a third electrode, the control unit includes a display mode switching unit, a gamma correction table memory unit, a gamma correction unit, and an image data output unit, the display mode switching unit switches between narrow viewing angle mode and wide viewing angle mode by controlling a voltage applied to the third electrode, the gamma correction table memory unit contains gamma correction tables by each of which a gray level is associated with an application voltage to the first electrode and / or the second electrode, the gamma correction unit acquires different gamma correction tables from the gamma correction table memory unit for the narrow viewing angle mode and for the wide viewing angle mode, performs gamma correction on original image data based on each of the gamma correction tables, and outputs resultant gamma-corrected image data to the image data output unit, and the image data output unit outputs a liquid crystal panel drive signal to the liquid crystal panel and adjusts the application voltage to the first electrode and / or the second electrode.

The application discloses a kind of fluorescent microscopic image intelligent enhancement method, device and readable storage medium, belong to medical image processing field.The purpose is to solve the problem of fluorescent image multi-channel fusion difficulty, pseudo-color mapping inaccuracy, RGB processing unevenness and parameter dependence experience.The method comprises: obtaining multi-channel image and separating;Perform pseudo-color mapping and synthesis based on wavelength physical characteristics, to obtain a composite image;Obtain the R, G, B three-channel target histogram features of standard library;The histogram specification of R, G, B three-channel independent of composite image is carried out;Using genetic algorithm, with target histogram similarity as target, adaptively optimize R, G, B three-channel independent Gamma parameter;The optimal parameter is applied to independent Gamma correction, to obtain final enhanced image.The application realizes physical accurate mapping, standardization correction and parameter adaptation, and improves image quality.

The invention discloses a color correction method and system for a PDS programmable digital spectrum.The color correction method for the PDS programmable digital spectrum.The color correction method for the PDS programmable digital spectrum.The method comprises the steps that actually-measured spectrum data of an LED light source under different driving values are obtained, the mapping relation between the driving values and the actually-measured values is constructed, and a 3 * 3-dimensional correction matrix and an inverse matrix are calculated; matrix transformation and range clamping are carried out on the target RGB value, and accurate color output in a wide spectrum range is achieved in combination with gamma correction. By constructing the RGB color correction model and combining with the least square method to calculate the color correction matrix, accurate regulation and control of the spectrum of the LED light source are achieved, and the problems that in the prior art, spectrum correction is low in accuracy, poor in universality and insufficient in real-time performance are solved.

The invention provides a mine image enhancement model fused with multiple attention mechanisms, which comprises an input module, a contrast stretching layer module, a Gamma correction module, a real-time brightness interference module, a reflectivity enhancement network and an output module, and is characterized in that a multi-scale feature extraction module RFB-Bottleneck is combined in an adopted encoder-decoder architecture; through parallel fusion of feature maps of different scales, complex texture details in a mine image are captured, a neighborhood attention module DiNAT is also fused, so that the receptive field is expanded, global and local effective features are captured, lightweight is accelerated, the calculation amount is further reduced, and meanwhile, a space attention mechanism and a channel attention mechanism are introduced, so that the real-time performance of the mine image is improved. A multi-scale attention module MCAM is formed, a space attention mechanism mainly focuses on a key area in an image, channel attention mechanism enhancement is more helpful for image enhancement, the model can more comprehensively process the complex degradation problem of the mine image through combination of the space attention mechanism and the channel attention mechanism, and the enhancement effect is improved.

The invention belongs to the technical field of taillight control, and provides a multi-pixel taillight control system and method, and the method comprises the steps: determining a to-be-optimized duty ratio data set, and carrying out the integration to obtain a duty ratio-actual physical brightness corresponding table of each LED pixel; according to a duty ratio instruction output by Gamma correction and in combination with a to-be-optimized duty ratio data set, whether LED pixel duty ratio intervention taking a brightness uniformity requirement as a target needs to be carried out or not is judged; if yes, duty ratio pre-adjustment analysis of different LED pixels under brightness consistency is carried out, and an LED pixel reference object is determined; the actual physical brightness of the LED pixel reference object serves as an intervention reference, the target duty ratio or the target duty ratio sequence of each LED pixel needing to be adjusted is determined, the duty ratio instruction of Gamma correction on each LED pixel needing to be adjusted is corrected, and it is ensured that the tail lamp presents the highly-uniform visual lighting effect under the brightness level.

A high-concealment signal detection method, system, device and medium based on a digital residual image, the sampled signal IQ data is preprocessed, that is, the key parameters including the observation bandwidth (that is, the sampling rate), the frame length, the overlap rate and the time and frequency resolution are set; at the same time, each frame of signal is subjected to windowing filtering processing, and the system automatically determines the segmentation number according to the signal length; then, each signal segment is subjected to fast Fourier transform, and the calculation result is stored in a bitmap database; then, the frequency spectrum data is continuously superimposed in the bitmap database, based on the total superposition number, the proportion of each cell is calculated to form a probability density distribution matrix, the probability density distribution matrix is subjected to normalization processing, and all probability values are ensured to be located between 0 and 1; by using a self-defined mapping table, the normalized probability density matrix is converted into a digital residual image through linear mapping; finally, by using a method combining Gamma correction and median filtering, the digital residual image obtained through mapping is further enhanced, and a final clear and smooth digital residual image is obtained; in the application, the Gamma correction can effectively enhance the darker part to improve the image contrast, the median filtering can effectively remove the salt and pepper noise generated by image mapping, and the important edges and details of the signal in the image are retained; due to the low calculation complexity, the application is suitable for real-time processing and meets the low complexity requirement.

The present application relates to the technical field of data processing, and provides a task execution optimization method and system based on an environmental protection law enforcement inspection intelligent terminal. The method comprises the following steps: obtaining core performance indexes of the environmental protection law enforcement inspection intelligent terminal, and calculating a comprehensive performance score by using a nonlinear dynamic evaluation algorithm; obtaining ambient light intensity and the temperature of the environmental protection law enforcement inspection intelligent terminal, and calculating a saturation degree dynamic adjustment amount of the screen; calculating a screen contrast dynamic gamma correction amount according to the comprehensive performance score and the ambient light intensity, so as to adjust the brightness and contrast of the screen of the environmental protection law enforcement inspection intelligent terminal; obtaining a task queue to be executed, and evaluating the estimated resource consumption, subsequent dependency degree and historical risk coefficient of each task to be executed, so as to calculate the comprehensive priority weight of each task; and preferentially executing tasks with high comprehensive priority weight.

The invention discloses a cross-modal lightweight colorectal tumor segmentation method and device, and aims to solve the problems that an existing medical image segmentation model depends on large-scale annotation data, small lesions and fuzzy boundaries are inaccurately recognized, the calculation complexity is high, clinical deployment is difficult, and the like. According to the method, on the basis of an improved U-shaped network architecture, adaptive histogram equalization and Gamma correction are introduced in a data preprocessing stage to enhance boundary information of a low-contrast CT image; the encoder captures a multi-level context by adopting a multi-scale convolution and cavity convolution fusion module, and strengthens tumor edge response in combination with a boundary attention module; and meanwhile, the calculation amount is reduced by introducing rapid spatial pyramid pooling. The decoder effectively recovers details and avoids artifacts through lightweight jump connection and bilinear interpolation up-sampling. The parameter quantity of the whole model is only about 4.25 M, the reasoning efficiency and the cross-equipment generalization ability are remarkably improved while the high segmentation precision is guaranteed, and the method is suitable for a resource-limited clinical environment.

The application belongs to the technical field of display, and particularly relates to a driving method of a display panel, a time sequence controller and the display panel. The driving method comprises the following steps: in a variable refresh rate mode, a change amplitude of a current refresh rate is obtained according to a vertical synchronization signal; when the change amplitude exceeds a preset threshold, voltage gain control data corresponding to the current refresh rate is generated; the voltage gain control data is packaged to obtain packaging data according to an effective window time length of a current vertical blanking area; and the packaging data is sent to a gamma correction chip through a special data transmission channel in the current vertical blanking area, so that the gamma correction chip adjusts output gamma voltage according to the received voltage gain control data; wherein the output gamma voltage is used for compensating the brightness of the panel in the variable refresh rate mode. The application effectively improves the poor display effect in the application process of the variable refresh rate mode.

The invention relates to a low-light scene infrared and visible light image rapid fusion method based on OpenCL, and belongs to the technical field of computer vision. According to the method, a low-light enhancement task of a visible light image and a fusion task of infrared and visible light images are subjected to combined modeling. Based on a brightness component of a color space, low light enhancement and gradient transfer are jointly optimized, and simple and effective enhancement fusion of an infrared image and a visible light image in a low-illumination night scene is realized. The invention provides a complementary logarithmic gamma correction function, the ELGC realizes low light enhancement, the SLGC realizes high light suppression, and the ELGC and the SLGC interact with each other, so that the enhancement of general brightness in the daytime can be realized.

The application discloses a remote sensing image defogging method and device, equipment, storage medium and program product, and relates to the technical field of image processing. The method comprises the following steps: acquiring a remote sensing image in fog, and performing preprocessing on the remote sensing image in fog based on an atmospheric scattering model to generate a preprocessed image; performing gamma correction on the preprocessed image to generate a plurality of exposure adjustment images, and generating a global enhancement image based on the plurality of exposure adjustment images; performing enhancement processing on a local image block in the preprocessed image based on an enhancement control factor to generate a local enhancement image; and fusing the global enhancement image and the local enhancement image to obtain a defogging remote sensing image. Through the above method, high-frequency edge details and low-frequency degradation areas are processed respectively, so that more effective defogging is realized.

The application discloses a kind of faint light image enhancement methods based on parameter estimation, belong to computer vision, machine learning and other fields.Utilize depth separable convolution and the parameter of optimization network of reverse residual structure, the ability of network to the extraction of channel and spatial dimension feature is guaranteed, while the calculation amount and parameter amount of convolution operation are reduced.Then, the scaling point attention mechanism that can capture global information of feature is used to estimate color correction matrix and gamma correction parameter, realizes the overall optimization to final imaging quality.In the network training process, the L2 loss of pixel-level difference and the perception loss of multi-weight cognitive-level difference are used.The experiment of the application on LoL dataset shows that when the expansion rate of reverse residual structure is 1.5, the optimal performance can be achieved on LoL dataset.

A gamma correction method for a display device determines a first voltage code for a first color corresponding to each of grayscale values based on a target gamma value and a target color coordinate at a reference measurement point, generates a first lookup table including the first voltage code for the first color, determines a second voltage code for the first color corresponding to each of the grayscale values based on the target gamma value and the target color coordinate at a correction measurement point, generates a first color position correction value based on the first voltage code for the first color and the second voltage code for the first color, and performs gamma correction using the first color position correction value and the first lookup table.