Abstract: A device includes an electronic processor configured to define a first set of sample pixels from a set of sample pixels determined from received video data according to a first electro-optical transfer function (EOTF) in a first color representation of a first color space; convert the first set of sample pixels to a second EOTF via a mapping function, producing a second set of sample pixels according to the second EOTF; convert the first and second set of sample pixels from the first color representation to a second color representation of the first color space; determine a backward reshaping function by repeatedly applying and adjusting a sample backward reshaping function so as to minimize a difference between predicted pixel values obtained by applying the sample backward reshaping function to the pixels of the converted first set and the pixels of the converted second set.

Abstract: Different candidate image data feature types are evaluated to identify one or more specific image data feature types to be used in training a prediction model for optimizing one or more image metadata parameters. A plurality of image data features of the one or more selected image data feature types is extracted from one or more images. The plurality of image data features of the one or more selected image data feature types is reduced into a plurality of significant image data features. A total number of image data features in the plurality of significant image data features is no larger than a total number of image data features in the plurality of image data features of the one or more selected image data feature types. The plurality of significant image data features is applied to training the prediction model for optimizing one or more image metadata parameters.

Abstract: Methods and systems for generating an interpolated reshaping function for the efficient coding of high-dynamic range images are provided. The interpolated reshaping function is constructed based on a set of pre-computed basis reshaping functions. Interpolation schemes are derived for pre-computed basis reshaping functions represented as look-up tables, multi-segment polynomials, or matrices of coefficients in a multivariate, multi-regression representation. Encoders and decoders using asymmetric reshaping and interpolated reshaping functions for mobile applications are also presented.

Abstract: Methods and systems for mapping images from a first dynamic range to a second dynamic range using a set of reference color-graded images and neural networks are described. Given a first and a second image representing the same scene but at a different dynamic range, a neural network (NN) model is selected from a variety of NN models to determine an output image which approximates the second image based on the first image and the second image. The parameters of the selected NN model are derived according to an optimizing criterion, the first image and the second image, wherein the parameters include node weights and/or node biases for nodes in the layers of the selected NN model. Example HDR to SDR mappings using global-mapping and local-mapping representations are provided.

Abstract: Methods and systems for image denoising when displaying high-dynamic-range images are described. Given an input image in a first dynamic range, and an input backward reshaping function mapping codewords from the first dynamic range to a second dynamic range, wherein the second dynamic range is equal or higher than the first dynamic range, statistical data based on the input image and the input backward reshaping function are generated to estimate the risk of noise artifacts in a target image in the second dynamic range generated by applying the input backward reshaping function to the input image. Using a measure of the variance in codeword bins in histograms of consecutive input frames (denoted as temporal histogram variance), a modified backward reshaping function is generated, which when applied to the input image to generate the target image eliminates or reduces noise artifacts in the target image.

Abstract: Methods and systems for frame rate scalability are described. Support is provided for input and output video sequences with variable frame rate and variable shutter angle across scenes, or for input video sequences with fixed input frame rate and input shutter angle, but allowing a decoder to generate a video output at a different output frame rate and shutter angle than the corresponding input values. Techniques allowing a decoder to decode more computationally-efficiently a specific backward compatible target frame rate and shutter angle among those allowed are also presented.

Abstract: Methods and systems for reducing banding artifacts when displaying high-dynamic-range images are described. Given an input image in a first dynamic range, and an input backward reshaping function mapping codewords from the first dynamic range to a second dynamic range, wherein the second dynamic range is equal or higher than the first dynamic range, statistical data based on the input image and the input backward reshaping function are generated to estimate the risk of banding artifacts in a target image in the second dynamic range generated by applying the input backward reshaping function to the input image. Separate banding alleviation algorithms are applied in the darks and highlights parts of the first dynamic range to generate a modified backward reshaping function, which when applied to the input image to generate the target image eliminates or reduces banding in the target image.

Abstract: Methods and systems for frame rate scalability are described. Support is provided for input and output video sequences with variable frame rate and variable shutter angle across scenes, or for input video sequences with fixed input frame rate and input shutter angle, but allowing a decoder to generate a video output at a different output frame rate and shutter angle than the corresponding input values. Techniques allowing a decoder to decode more computationally-efficiently a specific backward compatible target frame rate and shutter angle among those allowed are also presented.

Abstract: In some embodiments, an encoder device is disclosed to receive an input video stream containing images in a first dynamic range including a first image. The device receives a second image representing the first image. The device obtains statistical data for the first and the second images. The device determines, at a first time delay, a scene cut data from the input video stream and storing the scene cut data in a first sliding window. The device determines, at a second time delay, a first smoothing mapping function based on a second sliding window and the determined scene cut data. The device determines, at a third time delay, a second smoothing mapping function based on a third sliding window and the determined scene cut data. The device generates, at the third time delay, a composer metadata for the first image based on the first and second smoothing mapping functions.

Abstract: A standard dynamic range (SDR) image is received. Composer metadata is generated for mapping the SDR image to an enhanced dynamic range (EDR) image. The composer metadata specifies a backward reshaping mapping that is generated from SDR-EDR image pairs in a training database. The SDR-EDR image pairs comprise SDR images that do not include the SDR image and EDR images that corresponds to the SDR images. The SDR image and the composer metadata are encoded in an output SDR video signal. An EDR display operating with a receiver of the output SDR video signal is caused to render an EDR display image. The EDR display image is derived from a composed EDR image composed from the SDR image based on the composer metadata.

Abstract: Methods and systems for reducing banding artifacts when displaying high-dynamic-range images reconstructed from coded reshaped images are described. Given an input image in a high dynamic range (HDR) which is mapped to a second image in a second dynamic range, banding artifacts in a reconstructed HDR image generated using the second image are reduced by a) in darks and mid-tone regions of the input image, adding noise to the input image before being mapped to the second image, and b) in highlights regions of the input image, modifying an input backward reshaping function, wherein the modified backward reshaping function will be used by a decoder to map a decoded version of the second image to the reconstructed HDR image. An example noise generation technique using simulated film-grain noise is provided.

Abstract: 3D mapping statistics are generated for a first image of a first dynamic range and a second image of a second dynamic range different from the first dynamic range. Multivariate multiple regression (MMR) coefficients are generated by solving an optimization problem formulated using an MMR matrix built with the 3D mapping statistics without a letterbox constraint, and used to generate chroma mappings for predicting chroma codeword values of the second image. It is determined whether a letterbox exists in the images. If so, it is determined whether the chroma mappings accurately predict chroma codeword values in the second image. A reconstructed image generated by a recipient device by backward reshaping one of the images is rendered by a display device operating in conjunction with the recipient device.

Abstract: Methods and systems for reducing banding artifacts when displaying images are described. Identified image bands are filtered using an adaptive sparse finite response filter, where the tap-distance in the sparse filter is adapted according to an estimated width of each image band. Image debanding may be performed across multiple pixel orientations, such as rows, columns, a 45-degree angle, or a ?45-degree angle. Given a threshold to decide whether sparse filtering needs to be performed or not, an iterative debanding process is also proposed.

Abstract: Sequence-level parameters are generated for an image frame sequence including sequence-level indicators for indicating metadata types present for each image frame in the sequence of image frames. Frame-present parameters are generated for a specific image frame in the sequence including frame-present indicators corresponding to the metadata types as indicated in the sequence-level parameters. The frame-present indicators identify first metadata types for which metadata parameter values are to be encoded in a coded bitstream as metadata payloads. The image frame sequence, the sequence-level parameters, the frame-present parameters and the metadata payloads are encoded in the coded bitstream. A recipient device can generate, from the specific image frame based partly on the metadata parameter values determined for the first metadata types, a target display image for a target display.

Abstract: Training image pairs comprising training SDR image and corresponding training HDR images are received. Each training image pair in the training image pairs comprises a training SDR image and a corresponding training HDR image. The training SDR image and the corresponding training HDR image in the training image pair depict same visual content but with different luminance dynamic ranges. Training image feature vectors are extracted from training SDR images in the training image pairs. The training image feature vectors are used to train backward reshaping metadata prediction models for predicting operational parameter values of backward reshaping mappings used to backward reshape SDR images into mapped HDR images.

Abstract: Methods and systems for generating an interpolated reshaping function for the efficient coding of high-dynamic range images are provided. The interpolated reshaping function is constructed based on a set of pre-computed basis reshaping functions. Interpolation schemes are derived for pre-computed basis reshaping functions represented as look-up tables, multi-segment polynomials, or matrices of coefficients in a multivariate, multi-regression representation. Encoders and decoders using asymmetric reshaping and interpolated reshaping functions for mobile applications are also presented.

Abstract: Methods and systems for frame rate scalability are described. Support is provided for input and output video sequences with variable frame rate and variable shutter angle across scenes, or for input video sequences with fixed input frame rate and input shutter angle, but allowing a decoder to generate a video output at a different output frame rate and shutter angle than the corresponding input values. Techniques allowing a decoder to decode more computationally-efficiently a specific backward compatible target frame rate and shutter angle among those allowed are also presented.

Abstract: Methods and systems for reducing banding artifacts when displaying high-dynamic-range images reconstructed from coded reshaped images are described. Given an input image in a high dyna mic range (HDR) which is mapped to a second image in a second dynamic range, banding artifacts in a reconstructed HDR image generated using the second image are reduced by a) in darks and mid-tone regions of the input image, adding noise to the input image before being mapped to the second image, and b) in highlights regions of the input image, modifying an input backward reshaping function, wherein the modified backward reshaping function will be used by a decoder to map a decoded version of the second image to the reconstructed HDR image. An example noise generation technique using simulated film-grain noise is provided.

Abstract: Methods and systems for image denoising when displaying high-dynamic-range images are described. Given an input image in a first dynamic range, and an input backward reshaping function mapping codewords from the first dynamic range to a second dynamic range, wherein the second dynamic range is equal or higher than the first dynamic range, statistical data based on the input image and the input backward reshaping function are generated to estimate the risk of noise artifacts in a target image in the second dynamic range generated by applying the input backward reshaping function to the input image. Using a measure of the variance in codeword bins in histograms of consecutive input frames (denoted as temporal histogram variance), a modified backward reshaping function is generated, which when applied to the input image to generate the target image eliminates or reduces noise artifacts in the target image.

Abstract: Methods and systems for reducing banding artifacts when displaying high-dynamic-range images are described. Given an input image in a first dynamic range, and an input backward reshaping function mapping codewords from the first dynamic range to a second dynamic range, wherein the second dynamic range is equal or higher than the first dynamic range, statistical data based on the input image and the input backward reshaping function are generated to estimate the risk of banding artifacts in a target image in the second dynamic range generated by applying the input backward reshaping function to the input image. Separate banding alleviation algorithms are applied in the darks and highlights parts of the first dynamic range to generate a modified backward reshaping function, which when applied to the input image to generate the target image eliminates or reduces banding in the target image.