20 results about "Color adaptation" patented technology

This invention discloses a method, system, device, and storage medium for generating camouflage images, belonging to the field of computer vision and image generation. It employs a hierarchical automatic annotation method based on a large visual language model to obtain camouflage image annotation data, guiding the process through a three-level annotation workflow: online batch processing, offline supplementation, and manual review, outputting structured results. Based on a diffusion model framework, it integrates two types of feature enhancement modules—texture prior and color adaptation—to construct a generative model. After training with annotation data, it inputs the camouflage image to be restored, constraining texture consistency and aligning global color consistency through the two modules respectively, thus completing the generation and restoration of the camouflage image. This method for generating and restoring camouflage targets, combining semantic pairing, texture prior, and color consistency, along with its accompanying dataset, can be widely applied to camouflage target image synthesis, camouflage target detection enhancement, augmented reality, and other technical directions.

The invention discloses a self-adaptive ambient light matching method and system for the color temperature of an electronic whiteboard, ambient light information is collected through a common camera, the color characteristics of ambient light are sensed in real time in combination with an intelligent spectrum reconstruction algorithm and a color temperature matching strategy, and the color temperature displayed by the electronic whiteboard can be dynamically matched with the ambient light, so that the color temperature of the electronic whiteboard can be dynamically matched with the ambient light. Comprising the following steps: 1, pre-constructing a strategy library in which a plurality of groups of color temperature-brightness parameters and matched scenes are stored; 2, acquiring an ambient light image through a wide-angle camera, and performing multi-frame average noise reduction and exposure calibration on the ambient light image to obtain an RGB measured value of ambient light; 3, based on a preset PCA spectrum basis vector library, reconstructing the RGB measured value of the ambient light into an ambient spectrum in a range of 380-780 nm by adopting a non-negative sparse regression algorithm; and 4, calculating an environment color temperature according to the reconstructed environment spectrum, selecting a color temperature-brightness parameter matched with the environment color temperature from a strategy library in combination with a CIE CAM02 color adaptation transformation model, and adjusting the electronic whiteboard.

This application discloses a color adaptation method and an electronic device. The electronic device has a shooting end and a display end. At the shooting end, the electronic device can capture a first original image under a first ambient color temperature, and generate and save a first image file based on the first original image. The first image file includes a first image and first metadata, which includes the first ambient color temperature, the expected white point color temperature of the first image when displayed under the first ambient color temperature, and the white point color temperature of the first image in the first image file. At the display end, the electronic device can generate and display a color-adapted first image based on a second ambient color temperature. The white point color temperature of the color-adapted first image is determined based on the aforementioned first metadata. Therefore, the electronic device can restore the image to the color temperature perceived by the human eye after color adaptation to the greatest extent possible, thereby providing users with a more realistic shooting and viewing experience.

The application discloses a kind of structure light three-dimensional measurement method based on continuous phase constraint, including constructing encoding stripe, project the encoding stripe and obtain corresponding image, project periodic stripe pattern with preset phase offset and obtain multiple images, and the phase information of each pixel is calculated by the multiple images;Determine the stripe period interval to which the pixel belongs based on the phase information, and based on the continuity of phase on space, the initial stripe order is corrected consistently, and the three-dimensional appearance of the measured object is recovered according to the corrected stripe order and phase information.The present application encodes by time domain, space domain and color domain, the present method significantly reduces the number of patterns that need to be projected, while ensuring measurement accuracy through color adaptation and phase-assisted decoding, and has stronger robustness for color surfaces.

A system, apparatus, and method for processing an image based on color constancy are provided herein. The method comprises the following steps: obtaining an image in a first color space; converting the image into data in a second color space; transforming the data using color adaptation; performing a first normalization on the transformed data, wherein the first normalization includes applying a dynamic spatial filtering technique to adjust the transformed data based on the light intensity; applying a set of filters to the normalized data, wherein the set of filters are convolved based on the normalized data associated with the image; performing a second normalization on the filtered data to obtain an illumination estimate of the image related to the filtered data; and outputting normalized data from the second normalization, where the normalized data maintains color constancy based on the illumination estimate, thereby removing illumination from the normalized data.

The invention discloses a multi-style differentiation graph lightening system and device of a sighting telescope, and relates to the technical field of sighting telescopes. Comprising a prism, a differentiation plate, a first LED lamp, a second LED lamp and a lens, the differentiation plate is provided with a first pattern and a second pattern which are concentric, and the surface of the second pattern is coated with a black shading coating. By independently controlling on-off and color switching of the two LED lamps, free switching of independent display of the first graph, independent display of the second graph and combined display of the first graph and the second graph can be achieved, and multi-color adaptation is supported. The device ensures light conduction and imaging effects by accurately assembling all parts. The dividers can be replaced to expand and differentiate pattern styles, the problem that a traditional sighting telescope is fixed in dividers and colors is solved, the dividers are adaptive to different sighting scenes, the sighting flexibility and accuracy are improved, and the dividers are suitable for various sighting telescope devices.

The invention relates to the technical field of color blindness diagnosis, and particularly provides a color blindness personalized interactive evaluation method and system based on augmented reality, and the method comprises the steps: building a color mapping relation between a physical color card and an augmented reality environment based on a standard illumination condition; generating a hue test task composed of a plurality of virtual color blocks corresponding to the color mapping relation through the augmented reality environment; based on a natural interaction mode, assisting the user in sorting the virtual color blocks and recording a sorting result to obtain color vision defect features; local or cloud quantitative analysis is carried out on the color vision defect features, color vision quantitative error parameters are calculated, a user color vision perception model is constructed, and the color vision defect type and severity level of the user are output based on the user color vision perception model; and outputting a color vision evaluation report and generating a targeted color optimization scheme according to the user color vision perception model, the color vision defect type and the severity level. According to the invention, a full-process solution from accurate evaluation to personalized color adaptation is provided for color blindness users.

The invention provides a textile color fastness intelligent evaluation method and system based on machine vision, and relates to the technical field of textile color fastness intelligent evaluation methods, and the method comprises the steps: respectively collecting images of a to-be-evaluated textile under each visible light spectrum, and obtaining a fusion spectrum image containing each spectrum feature; constructing a texture damage index of the to-be-evaluated textile; obtaining a chromaticity distortion index of the to-be-evaluated textile; and splicing the texture damage index and the chroma distortion index by adopting linear coupling to form a color feature parameter of the textile image, comparing the color feature parameter with a set threshold value, and sending out an early warning when the color feature parameter exceeds the threshold value. Different spectral information is fused through weight optimization, so that the capability of capturing subtle color change of the textile is enhanced; capturing fiber physical damage characteristics through gray level co-occurrence matrix contrast calculation; and through combination of color adaptation conversion and nonlinear conversion, light source influence is eliminated, and the color fading degree is accurately quantified.

The present disclosure provides an image processing method, device, storage medium and electronic equipment, and relates to the technical field of computer vision. The image processing method comprises: acquiring a to-be-displayed image and spectral data of a plurality of detection regions collected by a plurality of spectral sensors; determining response data of each sub-region in XYZ color space according to the spectral data of each detection region and a human eye response function, determining a first conversion parameter of each sub-region according to the response data of each sub-region in XYZ color space and the response data of each sub-region in RGB color space; determining a color adaptation conversion parameter in an LMS color space based on brightness information and color temperature information of a display environment of the to-be-displayed image; determining a color transformation parameter of each sub-region according to the first conversion parameter, the color adaptation conversion parameter and a second conversion parameter; and performing color transformation processing on the to-be-displayed image by using the color transformation parameter. The present disclosure improves the image processing efficiency.

The application belongs to the technical field of image processing, and discloses a color adaptation driving white balance correction method and device suitable for a single light source, electronic equipment and a storage medium, which can improve the accuracy of image white balance correction. The method specifically comprises the following steps: using a characteristic matrix and a cone response transformation matrix of an image acquisition device, converting chrominance values of a captured image and chrominance values of an ambient light source into image LMS cone response and ambient light source LMS cone response values respectively; calculating a gain coefficient of each cone channel based on the ambient light source LMS cone response value and a reference light source LMS cone response value; using the gain coefficient and the image LMS cone response, calculating corresponding colors of the captured image under the reference light source; and using an inverse matrix of the characteristic matrix and the cone response transformation matrix, converting the corresponding colors to realize white balance correction of the captured image.

The present application relates to a convolutional neural network-based image color fusion method, device and storage medium, applied to the technical field of image processing, comprising: realizing color adaptation of foreground and background under the double constraints of foreground mask and skin segmentation mask through a color fusion model, optimizing the color naturalness of the skin area, effectively solving the problems of rigid fusion and strange skin color in the prior art, and improving the stability of the method; The high-resolution processing strategy of "low-resolution inference + detail preservation color migration" not only avoids the problems of large video memory consumption and long time consumption of direct high-resolution inference, but also solves the problems of loss of global color information in block inference and introduction of edge abnormalities in traditional high-frequency information recovery; The detail preservation color migration model can accurately extract the color features of the low-resolution fusion result and completely retain the texture details of the high-resolution original image, realizing the dual goals of color fusion and detail preservation; Automatic processing significantly reduces time and labor costs.

The invention relates to the technical field of image data processing, and discloses an infrared image enhancement method, device and equipment and a storage medium, which are used for the generalization ability of infrared image enhancement and the authenticity of a generated image. The infrared image enhancement method comprises the following steps: acquiring a data pair set formed by point cloud data generated by simulation and corresponding infrared images and a to-be-enhanced target image, selecting a target object data pair from the set, extracting an image area and point cloud projection information of the target object data pair in a simulation image, and projecting point cloud to a target image coordinate system according to the information, and accurately positioning a pasting position and a bounding box, carrying out background removal, color adaptation, texture blurring and edge feathering processing on an original image region, generating a fused and optimized object image, and pasting the fused and optimized object image to a specified position of a target image.

The application discloses a multi-style differentiation pattern lighting system and device of a sighting telescope, and relates to the technical field of sighting telescopes. The device comprises a prism, a differentiation plate, a first LED lamp, a second LED lamp and a lens. The differentiation plate is provided with a first pattern and a second pattern in a concentric manner, and the surface of the second pattern is coated with a black light-shielding coating. The opening and closing and color switching of the two LED lamps are independently controlled, so that the free switching of the first pattern display, the second pattern display and the combined display of the two patterns can be realized, and multi-color adaptation is supported. The device ensures the light transmission and imaging effect through precise assembly of the components. The application can expand the differentiation pattern style by replacing the differentiation plate, solves the problem of fixed differentiation pattern and color of the traditional sighting telescope, adapts to different sighting scenes, improves the sighting flexibility and accuracy, and is suitable for various sighting telescope devices.

The invention discloses an AI adaptive healthy lighting cooperative control system and method based on multi-modal physiological perception. The system comprises a multi-modal sensor module, an AI decision control module, a multi-channel LED driving module and a full-spectrum LED light source module. The method comprises the following steps: acquiring environment illumination intensity, color temperature, full spectrum distribution and human body existence and movement track data, and inputting the data into a pre-trained deep light color adaptation model; a pupil fluctuation response model, a spectrum fitting compensation algorithm and a crowd visual transient characteristic library are built in the model, environment parameters, human body states, time and crowd types are used as input, and cooperative control parameters of brightness, color temperature and ultrahigh frequency strobe frequency are dynamically decoupled and output. The integrated design of physiological perception, AI decision making, spectrum fitting and dynamic prediction is achieved, the visual comfort is improved, eyesight health is protected, and meanwhile energy consumption is reduced.

The invention discloses an animation color correction optimization system and method based on artificial intelligence, and relates to the technical field of color correction optimization. The system comprises a color data acquisition module, an AI analysis model training module, a dynamic correction module, a style matching module and an effect verification module. According to the method, animation frame color parameters and target style data are collected, a color analysis model based on deep learning is trained, real-time color correction is carried out for light change and element motion characteristics in a dynamic scene, correction parameters are adjusted in combination with an animation overall style, and color effect consistency is ensured through comparison and verification. According to the invention, the automatic and precise correction of animation colors is realized, the subjective error of manual operation is eliminated, the color adaptation effect in a dynamic scene is improved, the uniformity of animation color styles is ensured, and the method is suitable for the color optimization process of various animation production.

The invention discloses a screen rendering processing system and method based on a visual technology, and relates to the technical field of image processing. Illumination data and a panoramic image are analyzed to obtain a light source direction and an environment state; performing semantic segmentation on the rendered current frame screen by using a convolutional neural network, and searching an HDR region to generate a highlight candidate image; a protection weight is generated by using the current frame semantic mask graph and the highlight candidate graph, and comprehensive brightness adjustment is carried out through the adjusted basic tone mapping curve and the protection weight; adjusting the color of the current frame by using the adjusted color adaptation transformation matrix; adjusting a virtual light source in the current frame when the current frame screen is rendered according to the light source direction and the illumination intensity in the environment illumination; and integrating the basic tone mapping curve, the comprehensive brightness adjustment, the color adaptation transformation matrix and the virtual light source adjustment to construct the multifunctional rendering pipeline.

The invention relates to a color imaging method of multispectral imaging equipment and the multispectral imaging equipment. The color imaging method of the multispectral imaging equipment comprises the following steps: acquiring a multispectral image from a multispectral imaging sensor of the multispectral imaging equipment; calculating a tristimulus value of each pixel of the multispectral image in a predetermined color space to determine an object color tristimulus value and a white point tristimulus value of a source end; obtaining a preset white point tristimulus value of a target end; based on the white point tristimulus value of the source end and the white point tristimulus value of the target end, calculating an object color tristimulus value of the target end after color adaptation of the object color tristimulus value of the source end through a color adaptation transformation algorithm; and based on the target end object color tristimulus value, obtaining an imaging image of which color restoration is completed. In this way, accurate color imaging with the color closer to the color of a real subject is achieved.

The invention relates to an image processing method, circuit and device, electronic equipment and a chip, and the method comprises the steps: obtaining a to-be-processed original image, and obtaining a standard white point gain, a preference white point gain and a light source parameter; carrying out white balance correction on the original image by adopting a standard white point gain, and carrying out color correction on a white balance image obtained by white balance processing according to the light source parameters to obtain a color correction image; and performing color adaptation transformation processing on the color correction image according to the standard white dot gain and the preference white dot gain to obtain a target image. According to the invention, the standard white point gain is combined with the light source parameters to carry out white balance and color correction, the physical accuracy of image color restoration is guaranteed, the preference white point gain and the standard white point gain are introduced to carry out color adaptation transformation, stylized rendering conforming to the visual preference of human eyes is realized, and the image quality is improved. The interference on color correction based on preference white point gain in the prior art is effectively solved, and the color fidelity, stability and style flexibility of an imaging system are improved.

In order to restore the real color of the object in the image in the human eye due to the illumination color of different ambient light changing the color of the object in the image scene, the application discloses a color constancy algorithm based on gray surface extraction, which extracts the gray pixels in the image based on the illumination invariant vector, then uses the gray world algorithm on the pixels to predict the light source in the image, and corrects the color adaptation of the image. According to the color adaptation result, the gray pixels in the image are continuously detected and the color adaptation is carried out through iterative circulation until the set threshold is met, and the algorithm is stopped. Compared with the traditional algorithm, the illumination estimation accuracy is greatly improved.

The application discloses an intelligent color-changing light source system, and relates to the technical field of LED intelligent lighting; a power management module receives a mode switching instruction issued by a micro control module, and switches the operation condition according to the load demand corresponding to color output; a driving module receives a PWM pulse signal issued by the micro control module, and adjusts the driving current of an RGBW four-channel LED array module; a color perception module is used for collecting ambient light intensity, color temperature and color distribution data in real time, and transmitting the data to the micro control module for color adaptation and calibration; a closed-loop feedback adjustment module obtains color deviation through difference calculation based on the data collected by the color perception module, in combination with preset color parameters, and transmits the color deviation to the micro control module; the micro control module generates a calibration signal and sends the calibration signal to the driving module, so as to correct the driving current of each channel of the RGBW four-channel LED array module. The application can meet the requirements of low power consumption, fast response and high color precision.