111 results about "Standard dynamic range" patented technology

Video processing techniques and pipelines that support capture, distribution, and display of high dynamic range (HDR) image data to both HDR-enabled display devices and display devices that do not support HDR imaging. A sensor pipeline may generate standard dynamic range (SDR) data from HDR data captured by a sensor using tone mapping, for example local tone mapping. Information used to generate the SDR data may be provided to a display pipeline as metadata with the generated SDR data. If a target display does not support HDR imaging, the SDR data may be directly rendered by the display pipeline. If the target display does support HDR imaging, then an inverse mapping technique may be applied to the SDR data according to the metadata to render HDR data for display. Information used in performing color gamut mapping may also be provided in the metadata and used to recover clipped colors for display.

Video equalization including performing equalization such that a sequence of images have dynamic range (optionally other characteristics) that is constant to a predetermined degree, where the input video includes high and standard dynamic range videos and images from both. Equalization is performed with a common anchor point (e.g., 20% gray level, or log mean of luminance) input video and the equalized video, and such that the images determined by the equalized video have at least substantially the same average luminance as images determined by the input video. Other aspects are systems (e.g., display systems and video delivery systems) configured to perform embodiments of the equalization method.

Various embodiments provide tone mapping of images and video from one dynamic range to an available dynamic range of a display device while preserving or enhancing image details. According to one embodiment, an enhanced tone mapping module is configured to decrease a luminance of an image or video from a high dynamic range to a standard dynamic range. Conversely, according to one embodiment, an enhanced inverse tone mapper to increase a luminance of an image or video from a standard dynamic range to a high dynamic range.

The invention relates to an adaptive format conversion method based on high dynamic range video, comprising: acquiring parameters or user-defined parameters of a terminal display device through EDID (extended display identification data); setting a converter at the terminal display device to perform signal type conversion or video image processing on program signals, or setting an encoder at a server to re-encode the program signals so that the signals adapt to the terminal display device; receiving, by the terminal display device, a video file, or decoding, by the terminal display device, video bit streaming or the video file. The compatibility problem between HDR (high dynamic range) video and / or SDR (standard dynamic range) video program sources of different formats and different display devices is well solved, processing may be performed according to user-defined parameters, the program sources of different formats may also be adaptively displayed on different display devices in optimal state, steps for the display devices to set different parameters according to the different program sources are omitted, and operation is more facilitated for a user.

The invention discloses a high-dynamic range video processing method which comprises the following steps: detecting brightness values and contrast ratios of different scenes of a standard dynamic range (SDR) video so as to obtain a corresponding gamma value of each scene, further calculating according to the gamma values so as to obtain parameters for reverse tone mapping, and performing final conversion, so as to obtain high-dynamic range (HDR) video data. The method has the beneficial effects that the method is automatically applicable to most videos of different styles and different scenes, influence of brightness / contrast ratios in different scenes and areas in different conversion processes is taken into account, creation intentions of original content makers can be maintained in final conversion results to a very large extent, and very good image attractiveness and fidelity can be represented.

To enable a high quality HDR video communication, which can work by sending corresponding LDR images potentially via established LDR video communication technologies, which works well in practical situations, applicant has invented a HDR video decoder (600, 1100) arranged to calculate a HDR image (Im_RHDR) based on applying to a received 100 nit standard dynamic range image (Im_RLDR) a set of luminance 5 transformation functions, the functions comprising at least a coarse luminance mapping (FC), which is applied by a dynamic range optimizer (603), and a mapping of the darkest value (0) of an intermediate luma (Y′HPS), being output of the dynamic range optimizer, to a received black offset value (Bk_off) by a range stretcher (604), the video decoder comprising a gain limiter (611, 1105) arranged to apply an alternate luminance transformation function to 10 calculate a subset (502) of the darkest luminances of the HDR image, from corresponding darkest lumas (Y′_in) of the standard dynamic range image.

An electronic device and an image conversion method of the electronic device, the electronic device comprising: a receiving unit for receiving a first image from a source device; a decoding unit for decoding brightness information of the first image; a converting unit for converting a dynamic range of the first image on the basis of the decoded brightness information, using a mapping function; and a display unit for displaying a second image having the converted dynamic range on a display, wherein the mapping function is a curve function including a plurality of points determined on the basis of the first image, a characteristic of a change in brightness of a display of the source device, and a characteristic of brightness of a scene of the first image. The present disclosure may generate, for example, a high dynamic range (HDR) image, which is improved from a standard dynamic range (SDR) image.

The present invention provides a generative adversarial network-based high dynamic range inverse tone mapping method and system. The method includes the following steps that: an original high dynamicrange video is read, and the original high dynamic range video is cut and converted into data sets which can be used for training and are corresponding to a standard dynamic range and a high dynamic range respectively; a generative adversarial network is established based on a convolutional neural network and a hopping type connection is established, and standard dynamic range images are convertedinto high dynamic range images, namely inverse tone mapping is performed; and the entire generative adversarial network is continuously optimized according to a set comprehensive objective function,and a finally obtained network can complete mapping from the standard dynamic range to the high dynamic range. With the method of the invention adopted, the problems such as non-linearity insufficiency and complicated parameter adjustment of an existing non-learning method can be solved; the one-dimensional characteristic and gradient characteristic of the high dynamic range images are considered,so that inverse dynamic mapping of the high dynamic range can be better realized.

The invention provides a multi-exposure high-dynamic range inverse tone mapping model construction method and device. The multi-exposure high-dynamic range inverse tone mapping model construction method comprises the following steps: intercepting a high dynamic range image from an original high dynamic range video, converting the standard dynamic range images into standard dynamic range images, adjusting exposure time to generate multi-exposure standard dynamic range images, and forming a supervised data set by the standard dynamic range images with different exposures and a high dynamic rangeimage with the same normal exposure to serve as a training data set; establishing a generative adversarial network based on a convolutional neural network and skip connection; and establishing a target loss function integrated by the image content features, the intrinsic features and the perception features for the generative adversarial network, and continuously training and optimizing by adopting the training data set to obtain a final model. According to the multi-exposure high-dynamic range inverse tone mapping model construction method, the brightness of the overexposure or underexposureimage can be adjusted, and the effect of the generated high-dynamic-range image is improved, and the brightness characteristic and the chrominance characteristic of the high-dynamic-range image are considered, and inverse tone mapping of the high dynamic range is better achieved.

A transmission method in the present disclosure includes; obtaining an image and image signal characteristics information indicating one of an opto-electrical transfer function (OETF) or an electro-optical transfer function (EOTF) as image signal characteristics of the image; and transmitting a signal including the image and the image signal characteristics information. According to the transmission method in the present disclosure, a receiving device that received a high dynamic range (HDR) image and a standard dynamic range (SDR) image transmitted through broadcasting or the like can display these images appropriately.

The invention discloses a phase noise calibrating device based on a photoelectric fusion technique, which comprises a microwave amplifier (2), a power divider (3), a phase shifter (4), a modulator (5), an attenuator (6) and a phase noise measurement system (10), and further comprises a photoelectric oscillator (1), a microwave noise source (9), a broadband amplifier (8) and a band-pass filter (7). The photoelectric oscillator is developed through the photoelectric fusion technique, so the phase noise calibrating device has a large phase noise standard dynamic range and a simple structure, and can calibrate the phase noise measurement result precision, so the defects of the existing calibrating method are overcome, and thus, the phase noise measurement result precision traceability of a microwave frequency band is obtained.

Video equalization including performing equalization such that a sequence of images have dynamic range (optionally other characteristics) that is constant to a predetermined degree, where the input video includes high and standard dynamic range videos and images from both. Equalization is performed with a common anchor point (e.g., 20% gray level, or log mean of luminance) input video and the equalized video, and such that the images determined by the equalized video have at least substantially the same average luminance as images determined by the input video. Other aspects are systems (e.g., display systems and video delivery systems) configured to perform embodiments of the equalization method.

The present disclosure generally relates to a method and device of encoding a High Dynamic Range (HDR) color picture and at least one first Standard Dynamic Range (SDR) color picture, said method comprising encoding (101) a second Standard Dynamic Range (SDR) color picture obtained from the HDR color picture; According to the present disclosure, said method further comprises determining (102) at least one piece of color remapping information, from said second Standard Dynamic Range (SDR) color picture to said at least one first Standard Dynamic Range (SDR) color picture, said at least one piece of color remapping information being used to obtain an approximation of said at least one first Standard Dynamic Range (SDR) color picture from said second Standard Dynamic Range (SDR) color picture.

The invention provides a high dynamic range (HDR) signal processing system and a high dynamic range signal processing method, wherein the method and the device support an HDR display device and a standard dynamic range (SDR) display device. In the HDR signal processing system, a front processing module receives a first linear HDR signal and converts the first linear HDR signal to a first SDR signal and a first mapping signal. An encoding module receives the first SDR signal and the first mapping signal and performs encoding of the first SDR signal and the first mapping signal for obtaining a bit flow, thereby facilitating signal transmission. A decoding module receives and performs decoding of the bit flow for obtaining the first SDR signal and the first mapping signal. A back processing module receives the first SDR signal and the first mapping signal which are decoded from the bit flow and performs reconstruction for obtaining a first linear HDR signal, wherein the first SDR signal can be displayed through the SDR display device, and furthermore the first linear HDR signal can be displayed through the HDR display device.

The invention provides an image displaying method. The method comprises: acquiring standard-dynamic-range (SDR) data and performing encoding restoration processing on the SDR data to obtain original linear data corresponding to the SDR data; carrying out high-dynamic-range (HDR) transformation on the original linear data according peak brightness of an image display terminal to obtain non-linear data; and carrying out gamma presetting adjustment on the non-linear data to obtain HDR data and displaying a corresponding image based on the HDR data. In addition, the invention also provides an image display terminal and a computer readable storage medium. According to the invention, the original SDR content can be restored into the original linear data and then the original data are mapped again to obtain image data matching a target HDR display device, so that the SDR content is displayed at the HDR display device with the reasonable brightness; and the high dynamic characteristic of the HDR content is presented, so that the user experience is improved.

A method and an apparatus for coding at least one high dynamic range picture into a coded bitstream, and corresponding decoding method and apparatus are disclosed. The encoding method includes selecting a predetermined post-processing color correction function bp_det among a set of predetermined post-processing color correction functions bpset, according to at least one parameter computed from at least said high dynamic range picture, determining a pre-processing color correction function b0 from the selected predetermined post-processing color correction function bp_det, decomposing the high dynamic range picture, into a standard dynamic range picture, using the pre-processing color correction function b0, coding the standard dynamic range picture into the coded bitstream, coding at least one parameter for reconstructing the high dynamic range picture from the standard dynamic range picture decoded from the coded bitstream and a post-processing color correction function bp_dec.

The invention discloses a format conversion method for an HDR (High Dynamic Range) video, especially comprising the following steps: decoding an input HDR10 video to obtain data of a YCbCr color space; performing color space conversion on the obtained YCbCr data at a BT.2020 color gamut to obtain data of an RGB color space; respectively performing electro-optical conversion on color components inR / G / B channels; respectively processing the color components in the R / G / B channels according to the brightness of each pixel point by using mapping coefficients of tone mapping; respectively performing photoelectric conversion on the color components in the R / G / B channels in the step 4; performing color space conversion on the data of the RGB color space obtained through final processing to obtaindata of the YCbCr color space; and coding the YCbCr data obtained through the processing in the step 6 to obtain an SDR (Standard Dynamic Range) video stream. The format conversion method of the invention has the beneficial effects that: the HDR video can retain creation intention of an original content producer to a large extent, and a conversion result can present good image aesthetic feeling and fidelity.

The invention relates to an electronic device that dynamically controls standard dynamic range and high dynamic range content. The electronic device may be provided with a display. Standard dynamic range content and high dynamic range content may be generated by a content generator operating on a control circuit. Standard dynamic range content and high dynamic range content can be displayed at thesame time. The tone mapping parameters may be generated by a tone mapping engine for displaying standard dynamic range content and high dynamic range content. Tone mapping parameters may be selectedbased on factors such as ambient light levels, user brightness settings, content statistics, display characteristics, gaze point information, power consumption information, and each window information. Tone mapping parameters may be selected to accommodate simultaneous display of standard dynamic range content and high dynamic range content. The tone mapping parameter may be temporarily modified in response to a user gaze point switch between the standard dynamic range content and the high dynamic range content.

The invention relates to a multiple user-oriented dynamic range scalable coding method for HDR videos. The method comprises the steps of: firstly, proposing a dynamic range scalable model in consideration with HDR video sensing characteristics, and decomposing HDR videos of different dynamic ranges into standard dynamic range videos and a multiple residual signal frame sequence; then, quantizing and filtering the multiple residual signal frame sequence in combination with the luminance masking effect and the human eye sensing characteristics to filter out scattered data points in the residualand retain overall difference information between adjacent dynamic ranges of the residual signal frame sequence, thus improving the coding efficiency of the residual signal frame sequence; and finally, reconstructing the standard dynamic range videos and the HDR videos of all the dynamic ranges at a decoding end to adapt to a multi-user display device. The method also suppresses noise by using thevisual masking characteristic and improves the efficiency of dynamic range scalable coding.

Real-time forward reshaping, comprising selecting a statistical sliding window that indexes with the current frame, having also, a look-back frame and a look-ahead frame, determining whether they are part of the current scene, determining a noise parameter, a luma transfer function and a luma forward reshaping function based on the luma transfer function and the noise parameter within the current scene, selecting a central tendency sliding window of the current frame and the look-back frame within the current scene, and determining a central tendency luma forward reshaping function. The chroma reshaping comprises analyzing statistics for the extended dynamic range (EDR) weights and EDR upper bounds, mapping these to standard dynamic range (SDR) weights and SDR upper bounds based on the central tendency luma forward reshaping function, determining a chroma content-dependent polynomial and a central tendency chroma forward reshaping polynomial and generating chroma MMR coefficients.

In some aspects, the disclosure is directed to methods and systems for transformation between media formats, such as between standard dynamic range (SDR) and high dynamic range (HDR) media or between HDR media formats, without undesired hue shifting, via one or both of a luminance mapping ratio technique and a direct color component mapping technique.

A display apparatus may include a display, a storage configured to store a first output setting value corresponding to high dynamic range (HDR) content and a second output setting value corresponding to standard dynamic range (SDR) content, a communicator, and a processor configured to, while a first content is streamed through the communicator and displayed based on one of the first output setting value and the second output setting value that corresponds to the first content and in response to a second content being streamed through the communicator, control the display to change one of the first output setting value and the second output setting value to the other in phases and display the second content, and the first content may be one of the HDR content and the SDR content, and the second content may be the other of the HDR content and the SDR content.

The invention provides a video high dynamic range inverse tone mapping model construction method, which comprises the following steps of: cutting an original high dynamic range video into a pluralityof high dynamic range videos, converting the high dynamic range videos into standard dynamic range videos, and forming a supervised data set by the standard dynamic range videos and the high dynamic range videos to serve as a subsequent training data set; establishing a video generation network based on a three-dimensional convolutional neural network and skip connection; and establishing a targetloss function integrated by spatial features, time domain features, intrinsic features and perception features for the video generation network, and continuously training and optimizing by adopting the training data set to obtain a final network model. The invention also provides a corresponding construction device and a video high dynamic range inverse tone mapping method. According to the method, the problem of video flicker is solved, and the spatial characteristics, intrinsic characteristics and time domain characteristics of the high-dynamic-range video are considered, so that the inverse tone mapping of the high-dynamic-range video is better realized.

A circuit applied to a playback device includes an image format determining circuit, a control circuit, an image processing module and a blending circuit. The image format determining circuit receives an image signal and determines whether the format of the image signal is a standard dynamic range (SDR) or a high dynamic range (HDR) to generate a determination result. The control circuit generates a control signal according to the determination result. The image processing module selects an image processing setting corresponding to one of the SDR format and the HDR format, and processes the image signal according to the image processing setting to generate a processed image signal. The blending circuit superimposes an interface image onto the processed image signal to generate an output image signal to a display.

A method for converting a standard dynamic range (SDR) sequence into a high dynamic range (HDR) sequence is described. The method includes determining (S1) successive shots in the SDR sequence by cut detection, detecting (S2) if the SDR sequence comprises a sub-sequence of at least two successive short shots having a duration lower than D1, said subsequence comprising at least one bright shot having a luminance and a size greater than L1 and SZ1 respectively, and mapping (S3) the luminance range of bright shots of the detected subsequence from the low dynamic range to a first high dynamic range and mapping the other shots of the SDR sequence from the standard dynamic range to a second high dynamic range in order to generate the HDR sequence, the first high dynamic range having a maximal value Lmax1 lower than that of the second high dynamic range Lmax2.

Video processing techniques and pipelines that support capture, distribution, and display of high dynamic range (HDR) image data to both HDR-enabled display devices and display devices that do not support HDR imaging. A sensor pipeline may generate standard dynamic range (SDR) data from HDR data captured by a sensor using tone mapping, for example local tone mapping. Information used to generate the SDR data may be provided to a display pipeline as metadata with the generated SDR data. If a target display does not support HDR imaging, the SDR data may be directly rendered by the display pipeline. If the target display does support HDR imaging, then an inverse mapping technique may be applied to the SDR data according to the metadata to render HDR data for display. Information used in performing color gamut mapping may also be provided in the metadata and used to recover clipped colors for display.

The invention provides an image pixel sampling value conversion method and device as well as a sampling value processing method and device, which are used for converting a high-bit depth pixel sampling value into a low-bit depth sampling value. The image pixel sampling value conversion method comprises the steps of dividing a value range of the high-bit depth pixel sampling value into one or more segments and determining metadata of segment endpoints, wherein the metadata comprise high-bit depth pixel sampling values of the segment endpoints and corresponding low-bit depth sampling values; determining segments which the high-bit depth pixel sampling values in an image belongs to according to the metadata; and calculating the low-bit depth sampling values corresponding to the high-bit depth pixel sampling values based on the metadata of the segment endpoints. Through a processing way of converting the high-bit depth pixel sampling values into the low-bit depth sampling values, image color distortion and detail loss in mutual conversion of a video between a HDR (High Dynamic Range) and a standard dynamic range are reduced.

The invention discloses an automatic dynamic range detection method of a reflection scanner, which includes the following steps of building a color conversion lookup table; measuring CIE (international commission on illumination) Lab value of IT8.7 / 2 color target grey level and building a standard dynamic range table; scanning IT8.7 / 2 color target by grey level mode and building a dynamic range table of the scanner; scanning the IT8.7 / 2 color target by color mode and building a color component dynamic range table of the scanner; computing the dynamic range of the scanner and indistinguishable grey blocks and displaying results visually. By the automatic dynamic detection method, the dynamic range of the scanner can be detected automatically and completely, and quality evaluation and correct selection and use of the scanner are benefited.

At least some applications in the total HDR video chain desire some more sophisticated approach, such as a high dynamic range video encoder (900), arranged to receive via an image input (920) an input high dynamic range image (MsterHDR) which has a first maximum pixel luminance (PB_C_H50), the encoder being arranged to receive via a metadata input (921) a master luma mapping function (FL_50t1), which luma mapping function defines the relationship between normalized lumas of the input high dynamic range image and normalized lumas of a corresponding standard dynamic range image (Im_LDR) having a maximum pixel luminance of preferably 100 nit, characterized in that the encoder further comprises a metadata input (923) to receive a second maximum pixel luminance (PB_CH), and the encoder further being characterized in that it comprises: —a HDR function generation unit (901) arranged to apply a standardized algorithm to transform the master luma mapping function (FL_50t1) into a adapted luma mapping function (F_H2hCI), which relates normalized lumas of the input high dynamic range image to normalized luminances of an intermediate dynamic range image (IDR) which is characterized by having a maximum possible luminance being equal to the second maximum pixel luminance (PB_CH); an IDR image calculation unit (902) arranged to apply the adapted luma mapping function (F_H2hCI) to lumas of pixels of the input high dynamic range image (MsterHDR) to obtain lumas of pixels of the intermediate dynamic range image (IDR); and an IDR mapping function generator (903) arranged to derive on the basis of the master luma mapping function (FL_50t1) and the adapted luma mapping function (F_H2hCI) a channel luma mapping function (F_I2sCI), which defines as output the respective normalized lumas of the standard dynamic range image (Im_LDR) when given as input the respective normalized lumas of the intermediate dynamic range image (IDR); the encoder being further characterized to have as output: the intermediate dynamic range image (IDR), as first metadata the second maximum pixel luminance (PB_CH), as second metadata the channel luma mapping function (F_I2sCI); and as third metadata the first maximum pixel luminance (PB_C_H50).