181 results about "Tone mapping" patented technology

The invention discloses a high-precision image processing method and system based on illumination adaptive compensation, and relates to the technical field of computer vision and image processing, and the method comprises the steps: inputting an original image, and dividing the image into a high-frequency edge layer, an intermediate-frequency texture layer and a low-frequency illumination layer through a multi-scale residual network; acquiring illumination intensity, color temperature and scene categories in real time by using an ambient light sensor and a scene semantic segmentation model, and generating dynamic compensation parameters; carrying out dynamic range expansion on a low-frequency illumination layer based on a physical illumination model, and adjusting the weight of highlight suppression and dark area enhancement through a self-adaptive S-shaped exposure curve; a double-branch generative adversarial network is adopted, noise suppression and super-resolution reconstruction are carried out on the high-frequency layer, and texture detail enhancement is carried out on the intermediate-frequency layer; aligning the data of the depth camera and the infrared sensor with the visible light image through a cross-modal fusion module; and performing tone mapping on the fused image based on human visual characteristics, and outputting an enhanced image with a high dynamic range and reserved details.

The invention provides a pixel dynamic calibration method and device for a display, equipment and a storage medium. The method comprises the following steps: acquiring display parameters and a calibration image of the display; performing visual semantic analysis on the calibration image to generate a partition guidance mask, and marking a plurality of areas with different visual fidelity in the image by the partition guidance mask; generating a group of parallel region tone mapping curves for the plurality of regions based on the display parameters and the partition guide mask; performing synchronous processing on a corresponding region of the calibration image by using the region tone mapping curve to generate a partition mapping result, and fusing the partition mapping result into a correction image; generating a strategy execution record based on the partition guidance mask and the regional tone mapping curve; binding the strategy execution record with the content characteristics of the calibration image, and storing as a scene calibration strategy file; and when a new image frame is processed, calling the matched scene calibration strategy file for processing.

To employ low resolution, noisy tone mapping operations for high resolution images, at least one raw image frame is converted to a first image at a higher resolution and a second image at a lower resolution. Tone mapping is applied to the second image to derive a third image at the lower resolution. Histogram matching and regularization are performed to determine a lookup table approximating histogram matching of the second image to the third image. A global gain map is derived based on luma for the first image and the lookup table. A local gain map is derived by up-sampling and denoising residual differences between the third image and the lookup table applied to the second image. Based on the global gain map and the local gain map, a total gain map is determined for tone mapping the first image to produce a fourth image at the first resolution.

The invention discloses an HDR dynamic tone mapping method and system. The HDR dynamic tone mapping method comprises the following steps: S1, acquiring an ambient light parameter, a user interaction parameter and a display equipment state parameter which are acquired in real time; s2, performing dynamic parameter fusion on the ambient light parameters, the user interaction parameters, the display equipment state parameters and video content metadata to generate dynamic metadata; s3, generating a self-adaptive tone mapping curve based on the dynamic metadata, wherein the self-adaptive tone mapping curve adjusts a brightness mapping relation through an equipment aging compensation parameter; and S4, measuring the error between the actual display image quality and the theoretical value, and correcting the compensation parameter in the dynamic parameter fusion according to the error value. According to the method, various parameters are collected in real time, the adaptive tone mapping curve is generated through dynamic fusion, and errors are corrected in combination with closed-loop feedback, so that the problem of image quality degradation caused by environment change, equipment aging and user interaction difference in the traditional HDR technology is solved, and high-precision and adaptive dynamic display optimization is realized.

This disclosure provides a tone mapping method and apparatus. In the method, after global tone mapping is performed on a to-be-displayed image, local mapping information is adjusted to obtain the adjusted local mapping information; and based on the adjusted local mapping information, local tone mapping is performed on at least some pixels in the to-be-displayed image on which global tone mapping is performed. In embodiments of this disclosure, a global and local joint tone mapping solution is used, and local mapping is performed based on the adjusted local mapping information, to balance an uncoordinated contrast between different regions in local tone mapping, and effectively improve tone mapping effect and display effect of an image.

Disclosed is a method for enabling exposure-guided three-dimensional (3D) reconstruction, including (i) receiving Low Dynamic Range (LDR) input image captured by camera; (ii) rendering High Dynamic Range (HDR) image corresponding to input image, using HDR 3D reconstruction model pre-trained for HDR image reconstruction of 3D environment; (iii) applying HDR to LDR tone-mapping operator on HDR image, for producing tone-mapped LDR image; (iv) determining first loss function (FLF) between input image and tone-mapped LDR image, FLF comprising weighted pixel value differences between pixels of input image and corresponding pixels of tone-mapped LDR image; (v) determining whether input image has saturated pixel(s), saturated pixel(s) comprises: highlight saturated pixel, shadow saturated pixel; (vi) de-weighting pixel value difference corresponding to saturated pixel in FLF; (vii) back-propagating gradient of FLF with respect to model parameters, through differentiable render function of HDR 3D reconstruction model, for adjusting model parameters in way that reduces FLF.

The invention discloses a night enhanced imaging and dynamic denoising method for an automobile data recorder, relates to the technical field of vehicle-mounted image processing and computational photography, and is used for solving the problems of insufficient brightness and too strong noise of night videos of the automobile data recorder under a low-illumination condition. Estimating the zero-mean Gaussian noise intensity of a read link and the Poisson noise intensity increasing along with the brightness in the same frame, converting the zero-mean Gaussian noise intensity and the Poisson noise intensity into brightness equivalent parameters, and introducing a unified control function G as the scale reference of all enhancement and noise reduction links; defining a sharing priori H and carrying out unified constraint in dense optical flow, depth time sequence denoising and local tone mapping; and in combination with the motion mask and the background model, performing differential space-time denoising and proportional write-back, and in cooperation with motion blur detection, spatial variation motion kernel and constrained deconvolution and multi-frame detail recharge, obtaining target brightness and outputting an RGB frame after proportional write-back.

A computing system for generating a gain map-based enhanced High Dynamic Resolution (HDR) image receives an HDR image comprising a plurality of pixels, each pixel having one or a plurality of brightness values for each of a plurality of color components, applies at least a first tone mapping algorithm to each pixel in the HDR image, generates a gain map using the HDR image and the SDR image, generates a gain map-based enhanced HDR image based on the SDR image and the gain map, and generates an output based on the gain map-based enhanced HDR image.

The invention relates to the technical field of augmented reality, in particular to a 24-solar-term astronomical space-time presentation method and system based on mixed reality. The method comprises the following steps: firstly, reading augmented reality scene initialization data, configuring virtual scene parameters, and executing three-dimensional scene registration to generate a registration matrix; executing visual tracking by collecting an image stream, and generating a viewpoint transformation matrix; the system performs real-time sky semantic segmentation on an image stream to generate a binarized sky mask, and constructs an augmented reality rendering pipeline: synthesizing registration and viewpoint matrix calculation rendering operators, using the sky mask as an Alpha mask to perform pixel-level fusion of a virtual starry sky and a real sky, and combining sparse point clouds to perform depth occlusion synthesis, so as to obtain an augmented reality rendering pipeline. An atmospheric optical coloring model and a dynamic volume particle system are loaded for environmental atmosphere enhancement; and optical consistency fusion of a virtual image and a real environment is further realized through HDR luminosity alignment and tone mapping, and finally high-fidelity augmented reality superposition is realized.

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 low-illumination image enhancement method based on semantic perception and differentiable tone mapping, and belongs to the field of computer vision and image processing. According to the method, semantic information of each region in an image is extracted through a semantic segmentation network, different importance weights are distributed for different semantic regions, and then a differentiable tone mapping curve generation module is driven to dynamically adjust brightness and contrast enhancement parameters of each region. According to the system, an end-to-end trainable architecture is adopted, semantic perception loss, physical consistency loss and image quality loss are jointly optimized, and finally content self-adaptive enhancement of low-illumination images is achieved. Compared with the prior art, the problems of semantic information loss, overexposure or insufficient enhancement and the like in a traditional method are effectively solved. By introducing semantic perception driven by deep learning and differentiable tone mapping, the detail and color consistency of a semantic region can be more accurately kept in the image enhancement process. In the aspect of performance evaluation, the peak signal-to-noise ratio (PSNR) of the method is improved by more than 3.2 dB, the average intersection-to-union ratio (mIOU) of semantic segmentation is improved by more than 8.5%, and the method is remarkably superior to an existing mainstream image enhancement method.

This disclosure provides systems, methods, and devices for machine learning techniques that support image processing for use in a vehicle assistance system. In one aspect, a method is provided that includes receiving a first image frame captured from a camera positioned on a vehicle. The method further includes determining, based on the first image frame, a probability value that the first image frame depicts at least a portion of a windshield wiper blade. A time filter is determined based on the probability value, and an output image frame is determined by tone mapping a second image frame according to the time filter. Other aspects and features are also claimed and described.

In some examples, the method for tone mapping a high dynamic range (HDR) image to a lower dynamic range image (TDR) comprises obtaining a luminous intensity image based on the HDR image, processing the luminous intensity image using a feature extractor network, whereby to generate a feature map, processing the feature map using at least one neural network module of multiple neural network modules, obtaining a tone mapping operator based on an output of the at least one neural network module of the multiple neural network modules, and applying the tone mapping operator to the HDR image, whereby to obtain the TDR image, wherein the tone mapping operator comprises a tone mapping curve.

A video encoding device may determine whether to apply neural-network post-filter (NNPF) for tone mapping. The device may, based on a determination to apply NNPF, obtain at least one metadata parameter associated with NNPF tone mapping. The device may include, in video data, a neural-network post-filter tone mapping indication that NNPF for tone mapping is to be applied. A video decoding device may determine whether to apply NNPF for tone mapping based on a neural-network post-filter tone mapping indication. The device may, based on a determination to apply NNPF, determine at least one metadata parameter associated with NNPF tone mapping. The device may apply NNPF for tone mapping based on the at least one metadata parameter. The device may obtain an NNPF characteristics (NNPFC) tone mapping sub-purpose indication. The at least one metadata parameter associated with NNPF tone mapping may be determined based on the NNPFC tone mapping sub-purpose indication.

The invention relates to a tone mapping method and device, electronic equipment and a storage medium. According to the method, a first logical operation unit, a second logical operation unit, a third logical operation unit and a lookup table of a field programmable logic gate array are matched with one another. Specifically, by inputting the Y channel median value into the lookup table, the Y channel value adjustment coefficient can be directly obtained, and exponential operation between the Y channel median value and the Y channel value adjustment coefficient does not need to be carried out. By inputting the ratio of the Y channel value of each pixel stretched to the full domain to the median value of the Y channel of each pixel stretched to the full domain into the lookup table, the compression value of the Y channel can be directly obtained, and exponential operation of the ratio and the compression value of the Y channel is not needed, so that the data processing efficiency is improved, and the operation resources are saved.

The invention provides a halo suppression method and device during tone mapping, equipment, a medium and a product, and relates to the technical field of image processing. The halo suppression method during tone mapping comprises the following steps: acquiring a dynamic range compression curve of an image to be processed; calculating the target probability of each pixel point based on the pixel value of each pixel point in the to-be-processed image; the target probability represents the probability of whether the pixel point belongs to halo; based on the target probability of each pixel point, correcting the initial brightness value of the pixel point to obtain an updated brightness value of each pixel point; wherein the probability that the pixel point belongs to the halo is positively correlated with the amplification of the updated brightness value obtained by correction relative to the initial brightness value; and determining a respective mapping brightness value from the dynamic range compression curve based on the updated brightness value of each pixel point to obtain an output image.

Provided is an electronic device for, and method of, displaying an image, the electronic device including: a display; at least one processor; and memory storing one or more instructions that, when individually or collectively executed by the at least one processor, may cause the electronic device to: obtain an on-pixel ratio (OPR) based on input image data, determine a target luminance based on the OPR and a display set luminance, perform HDR tone mapping, using the target luminance, on the input image data, and control the display to display an image corresponding to the input image data on which HDR tone mapping is performed.

One embodiment provides a method comprising determining multi-dimensional metadata corresponding to an input image, and determining ambient light information indicative of an ambient light level in a surrounding environment of a display device. The multi-dimensional metadata includes a distribution function of pixels in the input image. The method further comprises determining one or more gains to adaptively compensate for the ambient light level in the surrounding environment based on the ambient light information. The method further comprises generating a tone mapping function based on the multi-dimensional metadata and the one or more gains, and applying the tone mapping function to the input image to generate a tone mapped image that is adaptively compensated for the ambient light level in the surrounding environment. The tone mapped image is provided to the display device for presentation.

This application provides a high dynamic range HDR video processing method, an encoding device, and a decoding device. The method includes: obtaining dynamic metadata of an Nth HDR video frame according to a dynamic metadata generation algorithm; calculating a tone-mapping (tone-mapping) curve parameter of the Nth HDR video frame based on the dynamic metadata of the Nth HDR video frame; generating a tone-mapping curve based on the curve parameter; determining, according to a quality assessment algorithm, distortion D′ caused by the tone-mapping curve; comparing D′ and DT, to determine a mode used by the Nth HDR video frame, where the mode is an automatic mode or a director mode, and DT is a threshold value; and determining metadata of the Nth HDR video frame based on the determined mode used by the Nth HDR video frame.

The application discloses a tone mapping method and device and a computer storage medium. The method comprises the following steps: acquiring first image data corresponding to a video image, and determining second image data corresponding to the video image based on a first mapping relationship and the first image data; wherein the first mapping relationship is used for electro-optical conversion and tone mapping; the video image is an HDR image; performing color gamut conversion based on the second image data to obtain third image data corresponding to the video image; and determining a tone-mapped image corresponding to the video image based on a second mapping relationship and the third image data; wherein the second mapping relationship is used for photoelectric conversion; and the tone-mapped image is an SDR image.

The application discloses a method and related device for image processing, obtaining a first feature map and a second feature map, the first feature map is used for describing high-frequency detail features of a target image, and the second feature map is used for describing low-frequency structural features of the target image, and the first feature map and the second feature map have the same size. The first feature map is subjected to first convolution processing to obtain a first enhancement result, and the second feature map is subjected to second convolution processing to obtain a second enhancement result. The first enhancement result and the second enhancement result are fused to obtain a first fusion result, and the first fusion result is used for generating an enhanced image of the target image. In the application, the high-frequency detail features and the low-frequency structural features of the target image are subjected to convolution processing respectively, wherein the convolution processing of the high-frequency detail features can optimize the detail features of the image, the convolution processing of the low-frequency structural features can optimize the tone mapping of the image, and through the fusion of the two different types of convolution results, the quality of image enhancement can be improved.

The application discloses a tone mapping method and system based on a lookup table and a Laplace filter, and belongs to the technical field of image processing.The input image is first decomposed into an adaptive Laplace pyramid;then a low-frequency image at the bottom layer of the adaptive Laplace pyramid is input into a weight predictor to obtain a pixel-level weight map, and a three-dimensional lookup table is used to perform three-linear interpolation on the low-frequency image to obtain a preliminary mapping image; then the preliminary mapping image and the weight map are fused pixel by pixel to generate an image at the bottom layer of the fine-tuned Laplace pyramid; then a filter parameter prediction module is used to learn a parameter value map of the remaining layer images of the adaptive Laplace pyramid, and the parameter value map is applied to a local Laplace filter to obtain the remaining layer images of the fine-tuned Laplace pyramid; finally, the fine-tuned Laplace pyramid is reconstructed to obtain a tone-mapped image.The application can retain local edge details of an image while performing global tone mapping.

Various implementations provide unvarnished video based on adjusting camera parameters according to environmental modeling. Environmental characteristics may be determined based on modeling a physical environment from sensor data captured via one or more sensors. For example, this may involve determining ambient light source optical characteristics, ambient surface optical characteristics, 3D mapping of the environment, user behavior, prediction of optical characteristics of light entering the camera, and the like. The method may involve determining camera parameters of an image captured via an image sensor based on environmental characteristics. For example, the method may determine exposure, gain, tone mapping, color balance, noise reduction, sharpness enhancement. The method may determine camera parameters based on user information (e.g., user preferences, user activity, etc.). The method may involve providing a transparent video of the physical environment based on the determined camera parameters.

The present invention relates generally to the field of video processing, and more specifically to high dynamic range (HDR) video and image processing. In particular, the present invention relates to determining one or more curve parameters of a tone mapping curve. For example, a device (encoder or decoder) can obtain a high dynamic range (HDR) video frame and metadata associated with the HDR video frame. The device can also obtain a pair of anchor points from the HDR video frame and the metadata. The pair of anchor points includes a first anchor point and a second anchor point of the tone mapping curve. Furthermore, the device can generate the one or more curve parameters of the tone mapping curve from the pair of anchor points.

Tone mapping methods and apparatus provide for receipt by a backend device may of metadata and an HDR image from a frontend device and the generation of a mapping curve based on feature parameters of the mapping curve included in the metadata. Tone mapping on the HDR image can be performed based on the mapping curve. The feature parameters of the mapping curve are determined by the frontend device based on a luminance distribution status of the HDR image. In this way, the mapping curve parameters are determined based on the luminance distribution status of the HDR image so that design of the mapping curve is more flexible, and display effect of the HDR image can be effectively improved.

Methods and systems for dynamic range conversion and display mapping of standard dynamic range (SDR) images onto high dynamic range (HDR) displays are described. Given an SDR input image, a processor generates an intensity (luminance) image and optionally a base layer image and a detail layer image. A first neural network uses the intensity image to predict statistics of the SDR image in a higher dynamic range. These predicted statistics together with the original image statistics of the input image are used to derive an optimal tone-mapping curve to map the input SDR image onto an HDR display. Optionally, a second neural network, using the intensity image and the detail layer image, can generate a residual detail layer image in a higher dynamic range to enhance the tone-mapping of the base layer image into the higher dynamic range.

Obtaining a processed spherical image includes obtaining a first luminance thumbnail image for a first hemispherical input image, obtaining a second luminance thumbnail image for a second hemispherical input image, obtaining a first distortion correcting weight map, obtaining a second distortion correcting weight map, obtaining, as an aggregate weighted mean value for the input spherical image, an aggregate of a first normalized weighted mean value for the first luminance thumbnail image and a second normalized weighted mean value for the second luminance thumbnail image, obtaining at least one of a target exposure value, a target aggregate gain value, or a region of interest ratio value in accordance with the aggregate weighted mean value, and obtaining the processed spherical image from the input spherical image in accordance with at least one of the target exposure value, the target aggregate gain value, or the region of interest ratio value.

A method is disclosed comprising modifying a color correction function intended to correct the initial chroma components of a current image to obtain normalized corrected chroma components to avoid clipping of the initial chroma components while maintaining saturation and preserving hue.

An image processing method includes obtaining a target picture and an initial tone mapping curve of the target picture, determining a plurality of interpolation points based on luminance information and / or dynamic metadata of the target picture, and determining a spline function that passes through the plurality of interpolation points, where the spline function is smoothly connected to the initial tone mapping curve at at least one of the plurality of interpolation points the initial tone mapping curve is modified based on the spline function to obtain a modified tone mapping curve of the target picture; and tone mapping is performed on the target picture based on the modified tone mapping curve. This image processing apparatus enables a display device to vividly and realistically reproduce a scene in a real world.

The invention provides a Unity-based image processing method, a storage medium and electronic equipment. The method comprises the steps of obtaining a Z-Buffer depth map of a to-be-rendered image; preprocessing the Z-Buffer depth map to obtain a depth-normal texture with an edge mark, a golden spiral sampling sequence and an AO parameter of a rendering object; based on the golden spiral sampling sequence and the AO parameters of the rendering object, performing multi-scale sampling on each pixel in the depth-normal texture to obtain a multi-scale sampling AO map; and based on the multi-scale sampling AO image, the historical frame AO image and the depth-normal texture, space-time filtering, edge enhancement and tone mapping are carried out, and a final processed AO image is obtained and output. Through the simple and efficient shadow effect implementation method, the performance consumption is reduced on the premise of ensuring the effect.