14 results about "Color balance" patented technology

This invention discloses a color balancing method, apparatus, electronic device, and storage medium. The method includes: acquiring four video images captured by a surround-view camera; performing distortion correction on the four video images to obtain four target video images; wherein the four video images are ultra-wide-angle images of the target object in four directions (front, back, left, and right); performing inverse perspective transformation on the four target video images to generate four top-view images; and performing color balancing on any one top-view image based on curve fitting to obtain the target top-view. This invention achieves color balancing through curve fitting, solving the problems of poor adaptability and low robustness of existing methods, and improving the adaptability and robustness of color balancing methods.

The application discloses a bubble detection, tracking and parameter quantification method and device based on an improved YOLOv8. The method comprises the following steps: collecting continuous frame visible light RGB bubble images; converting the RGB bubble images into LAB color space, performing adaptive enhancement on an L channel, performing color balance on A and B channels, and obtaining a pretreatment image after standardization and normalization processing; inputting the pretreatment image into an improved YOLOv8 bubble detection model, setting a multi-scale feature enhancement module after a P4 layer of the model, and adopting a bidirectional feature fusion structure and a decoupling detection head to output a bubble detection result; performing cross-frame association based on continuous frame detection results to obtain a bubble trajectory sequence; and calculating bubble aspect ratio and motion speed parameters according to a detection bounding box and the trajectory sequence. The application is suitable for bubble detection, tracking and parameter quantification analysis in a complex background.

The application discloses an image enhancement method and device, a storage medium and a computer program product. The method comprises the following steps: obtaining an original image, wherein the original image comprises a plurality of pixel points with a first pixel value; performing color balance processing on the first pixel value of each pixel point in the original image to obtain a first intermediate image, wherein the first intermediate image comprises a plurality of pixel points with a second pixel value, and the second pixel value is obtained by performing color balance processing on the first pixel value of the corresponding pixel point; performing contrast optimization on the second pixel value of each pixel point in the first intermediate image to obtain a second intermediate image, wherein the second intermediate image comprises a plurality of pixel points with a third pixel value; and performing gray scale adjustment on the third pixel value of each pixel point in the second intermediate image to obtain an enhanced target image. The application solves the technical problem that the visual quality and color restoration of an image after being enhanced by a related algorithm are poor.

The application provides a panoramic system chroma adjusting method, which comprises the following steps: acquiring images of each camera; determining overlapping areas of the images of each camera; selecting a first image as a reference image of a panoramic image and a second image as a to-be-stitched image in the overlapping areas; acquiring an initial homography matrix between the reference image and the to-be-stitched image; correcting the initial homography matrix to obtain an optimized homography matrix; stitching the reference image and the to-be-stitched image through a bilinear interpolation algorithm according to the optimized homography matrix to obtain a panoramic stitched image; and judging whether the color balance degree of the panoramic stitched image meets a preset value; if yes, panoramic image stitching is completed; otherwise, the color of the panoramic stitched image is adjusted. The application realizes color balance and uniformity of the panoramic stitched image and improves imaging quality.

One embodiment of the present invention relates to an artificial intelligence-based method, apparatus, and system for color correction of a photograph for printing, which uses artificial intelligence to predict the surface characteristics and ink absorption behavior of a printing medium and dynamically optimizes the color profile of the photograph accordingly. According to one embodiment, an AI-based photo color correction method for printing is provided, wherein the device includes a processor, memory, a communication module, and a non-transient storage medium, and the method is performed by the processor by executing a program stored in the non-transient storage medium, the method comprising: a step of acquiring an original photo file; a step of generating a preprocessed photo file by performing at least one of size adjustment, cropping, mosaic processing, color conversion, and black and white conversion on the original photo file; and a step of generating a corrected photo file by using an AI color correction model to automatically correct the saturation, brightness, and color balance of the preprocessed photo file and performing color conversion to correspond to a target color profile set to be suitable for print output.

This product is a remote control device for cameras that allows for remote monitoring and adjustment of parameters such as color balance.

The application relates to the technical field of building engineering information processing and application, and particularly provides a key information extraction method and system for building engineering files, which comprises the following steps: processing multiple source heterogeneous files into building engineering files, obtaining a first text through text analysis, and obtaining a second text through picture analysis; a model used for picture analysis is obtained by training an OCR model based on a domain fine-tuning strategy and a color balance strategy; inputting the first text and the second text into a screening model to obtain target text, wherein the screening model is obtained by training an initial model based on a mixed fine-tuning of a domain dataset and a general dataset, the domain dataset is obtained by processing a preselected dataset based on multiple semantic generalization strategies, and the initial model adopts a lightweight information extraction framework based on K-class global pointers; and inputting the target text into an extraction model to obtain key information. The method can solve the problem that, in the related art, when key information is extracted from building engineering files, it is difficult to balance the scalability, high precision and high efficiency.

Embodiments of the present application disclose an image-based data processing method, device, equipment and medium. The method comprises: extracting a gain of a specified color channel from an input image; obtaining a calibration gain matched with the gain, the calibration gain being obtained based on a calibration image collected under a calibration color temperature environment; calculating a gain error based on the calibration gain and a white balance gain with the green channel as a reference, and calculating a gain adjustment value based on the gain error and a historical gain error; and adjusting the specified color channel based on the gain adjustment value to obtain a target image. The technical solution of the present application improves the accuracy, efficiency, flexibility and the like of image color balance adjustment, and has high reliability in image-based data processing.

The application discloses a kind of underwater three-dimensional reconstruction differentiable rendering method based on optical degradation prior guidance.The application expands a three-item underwater imaging model, which explicitly separates the forward scattering from the direct transmission and backscattering.Second, to constrain the solution space of the inverse model, the application designs a kind of optical prior constraint physical reversibility regularization term.The mechanism uses a parallel, driven by optical prior variable physical constraint decomposition branch, to guide the learned neural degradation module to converge to physically valid and reversible solution.Finally, a physical information collaborative optimization strategy is introduced, which integrates optical induction bias such as light attenuation law and color balance with reconstruction loss.A large number of experiments on real and synthetic datasets show that the application effectively decouples scene appearance and medium effect, achieves the best performance in new view synthesis, intrinsic appearance restoration and geometric accuracy, and provides a robust solution for high-fidelity underwater scene reconstruction.

A technique for generating a digital photograph comprises blending two related images, each sampled according to a different illumination environment. The two related images are blended according to a blend surface function that includes a height discontinuity separating two different blend weight regions. Color consistency between the two related images is achieved by spatial color correction prior to blending. The technique enables a digital camera to generate a strobe image having an appearance of consistent color despite discordant strobe and ambient scene illumination.

The present application belongs to the technical field of image processing, and particularly relates to a method for generating pictures by intelligent shooting based on computer vision. The steps include: S1, collecting an initial image of a target person, using an improved YOLOv5 algorithm with a Neck layer introducing an attention module to identify key points and center coordinates of the person, calculating an offset and adjusting a shooting angle or position to obtain an initial composition; S2, detecting eye and limb states through key point detection, determining a shooting intention, and then shooting to obtain an original image; S3, calculating noise features by dividing the original image, classifying noise based on MobileNetV2, and denoising accordingly, and correcting mixed noise through a residual network; S4, segmenting image regions by using a full convolution network, optimizing by verifying an intersection-over-union ratio, fusing a mask, and generating a target picture by global color balance. The present application improves the composition accuracy, denoising effect and image quality, and meets the demand for high-quality intelligent shooting.

The application discloses an underwater image enhancement algorithm based on foreground and background principal component fusion and adaptive color correction. Specifically, first, a contrast enhancement strategy based on the maximum value of the percentile is implemented on the foreground image of the degraded image to generate a contrast-enhanced foreground sub-image. Then, a novel scoring formula is used to estimate the ambient light candidate region and a multi-layer transmission map is used to estimate the defogging strategy to generate a defogged background sub-image. Next, a principal component analysis fusion method is used to combine the advantages of foreground contrast enhancement and background restoration reconstruction to fuse a high-visibility underwater image. Finally, a color correction strategy guided by color balance is proposed to further correct the color of the fused image to improve the visual effect.