437 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.

A system for facilitating tone mapping is configurable to (i) generate an input image histogram based on one or more input images, the input image histogram comprising a plurality of bins, wherein each bin of the plurality of bins is associated with one or more pixel values and indicates a quantity of pixels that comprise the one or more pixel values; (ii) generate a target histogram based at least on the input image histogram; and (iii) generate an output image by using the target histogram to map pixel values of at least one of the one or more input images to corresponding pixel values in the output image.

A display device including: a display; and at least one processor connected to the display and configured to control the display device, where the at least one processor is configured to: identify an input image as a plurality of areas, identify a type of each of the plurality of areas by identifying at least one of the plurality of areas as a focus area and by identifying other areas of the plurality of areas as a background area, obtain a global tone mapping curve (TMC) for the input image based on a pixel level reduction amount corresponding to a target power consumption reduction amount, allocate a power consumption reduction amount to each of the plurality of areas based on the type of each of the plurality of areas, obtain a local tone mapping curve for each of the plurality of areas.

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.

The invention provides a display method and electronic equipment, and in the application, when the electronic equipment displays a picture, the shooting environment illumination of the picture, the brightness of a first gray scale of the picture in the shooting environment, and the brightness of a current watching environment can be obtained. The electronic equipment can determine the brightness of a first gray scale of a picture displayed in a display screen in a watching environment based on the shooting environment illumination, the display screen brightness in the shooting environment and the current watching environment brightness. And when the electronic equipment displays the picture, setting the brightness corresponding to each gray-scale value in the picture according to the brightness of the first gray scale of the picture in the determined watching environment. Besides, the electronic equipment can also obtain the brightness compression curve of the high dynamic range area in the picture, and perform tone mapping based on the brightness compression curve to restore the contrast ratio of the brightness of the pixel points in the high dynamic range area in the picture. Therefore, the contrast ratio of the highlight area in the picture displayed by the electronic equipment is higher, and the sense of reality is stronger.

The invention relates to the technical field of image shooting and processing, and discloses an anti-overexposure image processing method and system under strong light based on a high dynamic range, and the method comprises the steps: collecting a plurality of frames with different exposures for the same scene through an extremely weak light full-color night vision device, carrying out the multi-frame fusion, and generating a high dynamic range image; the method comprises the following steps: mapping an image with a high dynamic range to display equipment with a low dynamic range, and readjusting the brightness and contrast of the image to realize tone mapping; different areas in the image are independently processed, an overexposure area is identified, the brightness of the overexposure area is independently reduced, and the original brightness and contrast of other areas are kept; histogram equalization parameters are dynamically adjusted according to the local brightness distribution of the image, the image contrast and details are improved, and image color correction is achieved. The problem of overexposure of the ultra-weak light full-color night vision device in a strong light environment is solved through a high dynamic range algorithm, and the image quality of the night vision device under different illumination conditions is remarkably improved.

The invention relates to a high dynamic range image tone mapping method and device based on an attention mechanism. The method comprises the following steps: S1, determining a first brightness channel; the first brightness channel is a brightness channel of the high dynamic range image. And S2, adaptively adjusting the global brightness of the first brightness channel based on a channel attention mechanism to obtain a first brightness feature map subjected to global brightness mapping. And S3, enhancing local details of the first brightness feature map based on a self-attention mechanism to obtain a second brightness feature map. And S4, obtaining a second brightness channel according to the first brightness channel and the second brightness feature map. The second brightness channel is a brightness channel of the low dynamic range image. According to the method, adaptive brightness modification is realized based on channel attention, the flexibility of brightness mapping can be improved, detail retention in tone mapping is enhanced based on a self-attention mechanism, global brightness mapping and local detail enhancement can be effectively integrated, and a more excellent tone mapping result is obtained.

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.

A method includes receiving a quantized video having a first maximum luminance level or brightness associated with a mastering display with which the quantized video was mastered. The method also includes de-quantizing the quantized video in order to generate a de-quantized video. The method further includes applying a scene-adaptive tone mapping function to the de-quantized video in order to generate a tone mapped video. In addition, the method includes displaying the tone mapped video on a target display. The tone mapped video has a second maximum luminance level or brightness associated with the target display, and the second maximum luminance level or brightness is less than the first maximum luminance level or brightness.

A method includes obtaining a high dynamic range (HDR) image and generating low dynamic range (LDR) images based on the HDR image, where at least some of the LDR images are associated with different exposure levels. The method also includes generating tone-type weight maps based on the LDR images, where at least one of the LDR images is associated with two or more of the tone-type weight maps. The method further includes generating blending weights for the LDR images based on the tone-type weight maps, where the blending weights for at least one of the LDR images are based on at least two tone-type weight maps associated with at least two of the LDR images.

A non-transitory computer-readable storage medium stores executable instructions that, when executed by a processor, cause performance of operations comprising operations to access an image captured by an image sensor, obtain a transfer function for mapping pixel values, determine a faces indication that reflects a proportion of a scene depicted in the image that includes one or more human faces, and modify the transfer function based on the faces indication. Modifying the transfer function based on the faces indication comprises adjusting a gain of the transfer function to move the gain closer to unity. The operations include to apply the transfer function to pixel values of the image to produce a tone mapped image and output the tone mapped image.

The invention provides a semantic segmentation method based on an HDR dynamic neural radiation field, and relates to the technical field of image segmentation. According to the semantic segmentation method based on the HDR dynamic neural radiation field, the segmentation capability of a two-dimensional visual large model on pictures and videos is utilized, the segmentation capability of the two-dimensional model is expanded to four dimensions, a hyper-parameter controlled tone mapping module is constructed, mapping from an HDR view to LDR is controlled, and the segmentation capability in an HDR scene is greatly improved; a mask deformation field network and a dynamic mask inverse rendering method are provided, expensive labeling does not need to be performed on a four-dimensional scene, and any object in the four-dimensional dynamic scene can be segmented by using a two-dimensional picture mask.

The invention discloses a high dynamic range image tone mapping method and device, a medium and a program product, and relates to the field of image processing. The method comprises the following steps: calculating a brightness logarithm and a large-scale texture layer logarithm of a high dynamic range image to enhance image details and generate a global detail enhanced image; the brightness distribution is optimized by counting the brightness histogram, cutting the abnormal brightness value and compensating the abnormal brightness value; determining the average brightness and the standard deviation of the low dynamic range image based on the optimized histogram, obtaining a normalized brightness grey-scale map, and performing local detail enhancement; and restoring the brightness of the enhanced image to an original HDR range, mapping a color channel, and merging color spaces to obtain a final LDR image. According to the method, the dynamic range of the high-dynamic-range image can be compressed, and meanwhile, the detail features and brightness distribution reasonability of the image are effectively kept, so that the subjective visual quality and user experience of the low-dynamic-range image are remarkably improved.

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.

A method comprising: obtaining (401) high dynamic range data; computing (402, 403) a first tone mapping curve from the high dynamic range data corresponding to low high dynamic range values of a combined tone mapping curve, the first tone mapping curve ending by a point, called first point, with an abscissa representative of a high dynamic range diffuse white and an ordinate representative of a standard dynamic range diffuse white, the combined tone mapping curve allowing obtaining standard dynamic range data from the high dynamic range data; and completing (404) the combined tone mapping curve with a second tone mapping curve for high standard dynamic range starting from the first point.

A HDR tone mapping system includes several modules. A semantic segmentation module is used to extract semantic information from the input image. An image decomposition module is used to decompose the input image to a high-bit base layer and a detail layer. A statistics module is used to generate statistics of pixels of the input image according to the semantic information. A curve computation module is used to generate a tone curve from the statistics. A compression module is used to compress the high-bit base layer to a low-bit base layer according to the tone curve, the statistics and the semantic information. A detail adjustment module is used to tune the detail layer according to the semantic information and the statistics to generate an adjusted detail layer. An image reconstruction module is used to combine the adjusted detail layer and the low-bit base layer to generate an output image.

The invention discloses an image coding method, an image decoding method and related devices, and belongs to the field of image processing. The method comprises the following steps: acquiring a first image, wherein the first image is an image needing tone mapping; based on the first image, determining position coordinates of a plurality of sampling points of a tone mapping curve corresponding to the first image through an optimization equation or a deep learning network model; and compiling the first image and the position coordinates of the plurality of sampling points into a code stream. According to the method, the optimization equation or the deep learning model is established based on at least one of the image contrast, the image brightness and the contrast human eye perception threshold, and the image needing tone mapping is coded through the optimization equation or the deep learning model. Therefore, the decoding end establishes the tone mapping curve based on the code stream and realizes tone mapping of the image, so that the display effect of the image is obviously improved.

The invention relates to the technical field of image processing, in particular to an image data desensitization method, device and equipment, and the method comprises the steps: extracting a to-be-processed image or a RAW domain image of a to-be-processed video stream; sequentially performing wide dynamic range processing, first Bayer noise processing and tone mapping processing on the RAW domain image to obtain a first processed image; obtaining a dynamic ROI detection model and a privacy grading model; based on the first processing image and the dynamic ROI detection model, a second processing image is output, and the second processing image is that a privacy area is marked on the first processing image; based on the second processing image and a privacy grading model, obtaining a privacy level comprehensive score of each privacy area; and determining a corresponding desensitization means based on the privacy level comprehensive score of each privacy area so as to carry out pixel level privacy processing on the second processing image, and realizing end-to-end security privacy protection by processing the RAW domain image of the video or the image.

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.

The invention provides an image processing method, and the method comprises the steps: carrying out the conversion processing of a to-be-processed YUV image in a first color gamut range, obtaining an RGB image in a second color gamut range, generating a target mapping function, and enabling the target mapping function to be a function obtained through the fusion processing of a first mapping function and a second mapping function, the first mapping function is a function obtained by performing histogram statistics according to a Y channel component of the to-be-processed YUV image, and the second mapping function is a preset function, and performing mapping processing on an image in the to-be-played video based on the target mapping function to obtain a target RGB image. According to the scheme, the RGB pixels are combined with the brightness, the brightness of the image after tone mapping is increased, and the image quality of the image is improved.

According to various embodiments of the present disclosure, the provided method comprises the steps of: receiving a Hot Plug Detection (HPD) signal from a sink device; receiving, from the sink device, first information related to an Extended Display Identification (EDID) or a DisplayID (DPID) or DisplayPort Configuration Data (DPCD); identifying second information related to High Dynamic Range (HDR) content; generating, on the basis of the second information and luminance support information for each patch size included in the first information, output content information obtained by applying source-based tone mapping to the HDR content; and transmitting the output content information to the sink device.

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.

A photoelectric conversion device has a plurality of pixels each of which is configured to include a sensor unit that generates a pulse at a frequency corresponding to a photon reception frequency, and a counter that counts a number of the pulses. The plurality of pixels are controlled such that a signal is generated based on a difference between count values for the counter between a start time and an end time for a plurality of different accumulation periods within a full frame period, and such that an image signal that is generated during a first accumulation period is output between a time from an end of the first accumulation period until an end of a second accumulation period. In addition, the photoelectric conversion device generates a mapping parameter and performs tone mapping processing on the image signal using the mapping parameter.

The invention discloses an equipment calibration method and device, computer equipment and a computer readable storage medium, and the method comprises the steps: calibrating a gamma curve of target display equipment when an HDR function module is in a closed state; after the gamma curve calibration is completed, the HDR function module is controlled to be started; and when the HDR function module is in the on state, calibrating the tone mapping curve of the target display equipment. By adopting the method, the color accuracy effect of the image output by the target display equipment can be improved.

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.

The invention discloses a self-adaptive high-dynamic-range image generation method in a chemical monitoring scene, and belongs to the technical field of high-dynamic imaging and computational imaging. Performing registration preprocessing on the acquired reference image based on a brightness consistency criterion; constructing a high dynamic range image generation network model, inputting the reference image into the model, performing feature extraction and fusion through a multi-scale network, and generating a high dynamic range image based on the fused features; performing tone mapping on the generated high dynamic range image based on a brightness consistency criterion; and comparing the generated high dynamic range image with a reference image, calculating a pixel-level loss function and multi-dimensional perception loss, and optimizing an image generation process through a back propagation training network model. According to the method, imaging details of different scales are captured through a multi-scale feature processing method, so that the generated image is better in brightness range and details, and the expressive force of the image under a complex illumination condition is ensured.

Systems and methods for providing a temporal noise reducer (TNR) architecture that improves TNR performance by adjusting for lighting differences between image frames. Temporal noise reduction is a core feature of a video processing pipeline, where TNR can be used to decrease noise in video streams. Some TNRs compensate for the motion of objects between frames, but lighting changes can also lead to additional noise. As an object's position moves from frame to frame, the lighting of the object may change. A lightweight tone-mapping and color-correction operator is added to the TNR feedback loop, matching the radiometric properties of a TNR reference frame to the radiometric properties of the current frame to compensate for radiometric differences, thereby increasing the effectiveness of TNR in handling incremental lighting changes and speeding up its response to abrupt lighting changes.

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 invention provides an image processing method and device, electronic equipment, a storage medium and a program product. The method comprises the following steps: acquiring a source domain image, and performing tone mapping on the source domain image to obtain a target domain image; performing brightness enhancement on the source domain image to obtain a brightness enhanced image; identifying a target object in the source domain image, and determining a first weight of the target object in the source domain image; determining a second weight of the target object in the brightness enhancement image and a third weight of the target object in the target domain image based on the first weight; and based on the second weight and the third weight, fusing the brightness enhanced image and the target domain image to obtain a fused image. According to the invention, the accuracy of image processing can be improved.