Abstract: Methods and systems for generating a set of forward and backward reshaping functions for the efficient coding of high-dynamic range (HDR) images are provided. Given an initial set of forward reshaping functions, output forward reshaping functions are constructed by a) using the forward reshaping functions to generate a first set of corresponding backward reshaping functions b) generating a second set of backward reshaping functions using a multi-segment polynomial representation with a common set of pivot points c) generating an output set of backward reshaping functions by optimizing the polynomial representation of the second set of backward reshaping functions to minimize gap values between consecutive segments and d) using the output set of backward reshaping functions to generate the output set of forward reshaping functions by minimizing the distance between original input HDR codewords and reconstructed HDR codewords.

Abstract: In a cloud-based system for encoding high dynamic range (HDR) video, a computing node is assigned to be a dispatcher node, segmenting the input video into scenes and generating a scene to segment allocation to be used by other computing nodes. The scene to segment allocation process includes one or more iterations with an initial random assignment of scenes to computing nodes, followed by a refined assignment based on optimizing the allocation cost across all the computing nodes. Methods to generate scene-based forward and backward reshaping functions to optimize video coding and improve the coding efficiency of reshaping-related metadata are also examined.

Abstract: Sample data and metadata related to spatial regions in images may be received from a coded video signal. It is determined whether specific spatial regions in the images correspond to a specific region of luminance levels. In response to determining the specific spatial regions correspond to the specific region of luminance levels, signal processing and video compression operations are performed on sets of samples in the specific spatial regions. The signal processing and video compression operations are at least partially dependent on the specific region of luminance levels.

Abstract: Given input HDR and SDR images representing the same scene, a prediction model to predict the HDR image from a compressed representation of the input SDR image is generated as follows: a) generate noise data based at least on the characteristics of the HDR image b) generate a noisy SDR image by adding the noise data to the SDR image c) generate an augmented HDR data set and an augmented SDR data set by using the input HDR and SDR images and the noisy SDR image d) generate a prediction model to predict the augmented HDR data set based on the augmented SDR data set and e) solve the prediction model according to a minimization-error criterion to generate a set of prediction parameters to be transmitted to a decoder together with a compressed representation of the input SDR image to reconstruct an approximation of the input HDR image.

Abstract: A method for distributing High Dynamic Range (HDR) content to playback devices for displaying images where the HDR content is encoded to an HDR bitstream and the HDR bitstream is subsequently decoded by a playback device. The HDR bitstream contains auxiliary metadata packets that are based upon the processing capability of the playback device.

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: A backward reshaping mapping table is initially generated as an inverse of a forward reshaping mapping table. The backward reshaping mapping table is updated by replacing the content-mapped luminance codewords with forward reshaped luminance codewords generated by applying a luminance forward mapping to the sampled luminance codewords. The luminance forward mapping is constructed from the forward reshaping mapping table. The backward reshaping mapping table and the luminance forward mapping are used to generate backward reshaping mappings for creating a reconstructed image from a forward reshaped image. The forward reshaped image is encoded, in a video signal, along with image metadata specifying the backward reshaping mappings. A recipient device of the video signal applies the backward reshaping mappings to the forward reshaped image to create the reconstructed image of the second dynamic range.

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: In an encoder, a high-dynamic range (HDR) image is encoded using a family of local forward reshaping functions selected according to an array of forward mapping indices (FMI) indicating which local forward reshaping function needs to be used for each pixel in the HDR image to generate a reshaped standard dynamic range (SDR) image. A decoder, given the reshaped SDR image, iteratively generates a reconstructed HDR image and estimated reshaped SDR images by adjusting a local FMI array and a local array of backward mapping indices (BMI) until an error metric related to the difference between the local BMI and FMI arrays and the difference between the estimate SDR images and the reshaped SDR image satisfy a convergence criterion. Techniques for generating families of local forward reshaping functions and local backward reshaping functions based on a global forward reshaping function are also presented.

Abstract: A source color grade and a destination color grade may be received by an end-to-end image mapping pipeline comprising forward and backward paths. Forward neural networks in the forward path may be applied to generate, from the source color grade, a forward reshaped color grade corresponding to the destination color grade. Backward neural networks in the backward path may be applied to generate, from the forward reshaped color grade, a backward reshaped color grade corresponding to the source color grade. An overall neural network cost function may be specified for the forward path and the backward path to generate a cost that may be used as a basis for determining operational parameters for the forward and backward neural networks.

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: Apparatus and methods for providing software and hardware based solutions to the problem of synthesizing noise for a digital image. According to one aspect, a probability image is generated and noise blocks are randomly placed at locations in the probability image where the locations have probability values that are compared to a threshold criterion, creating a synthesized noise image. Embodiments include generating synthesized film grain images and synthesized digital camera noise images.

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: Given an input image in a high dynamic range (HDR) which is mapped to a second image in a second dynamic range using a reshaping function, to improve coding efficiency, a reshaping function generator may adjust the codeword range of the HDR input under certain criteria, such as for noisy HDR images with a relatively-small codeword range. An example of generating a scaler for adjusting the HDR codeword range based on the original codeword range and a metric of the percentage of edge-points in the HDR image is provided. The adjusted reshaping function allows for more efficient rate control during the compression of reshaped images.

Abstract: A confidentiality preserving system and method for performing a rank-ordered search and retrieval of contents of a data collection. The system includes at least one computer system including a search and retrieval algorithm using term frequency and/or similar features for rank-ordering selective contents of the data collection, and enabling secure retrieval of the selective contents based on the rank-order. The search and retrieval algorithm includes a baseline algorithm, a partially server oriented algorithm, and/or a fully server oriented algorithm. The partially and/or fully server oriented algorithms use homomorphic and/or order preserving encryption for enabling search capability from a user other than an owner of the contents of the data collection. The confidentiality preserving method includes using term frequency for rank-ordering selective contents of the data collection, and retrieving the selective contents based on the rank-order.

Abstract: A first predictor is applied to an input image to generate first-stage predicted codewords approximating prediction target codewords of a prediction target image. Second-stage prediction target values are created by performing an inverse cascade operation on the prediction target codewords and the first-stage predicted codewords. A second predictor is applied to the input image to generate second-stage predicted values approximating the second-stage prediction target values. Multiple sets of cascade prediction coefficients are generated to comprise first and second sets of cascade prediction coefficients specifying the first and second predictors. The multiple sets of cascade prediction coefficients are encoded, in a video signal, as image metadata. The video signal is further encoded with the input image.

Abstract: A method for image segmentation includes (a) clustering, based upon k-means clustering, pixels of an image into first clusters, (b) outputting a cluster map of the first clusters (c) re-clustering the pixels into a new plurality of non-disjoint pixel-clusters, and (d) classifying the non-disjoint pixel-clusters in categories, according to a user-indicated classification. Another method for image segmentation includes (a) forming a graph with each node of the graph corresponding to a first respective non-disjoint pixel-cluster of the image and connected to each terminal of the graph and to all other nodes corresponding to other respective non-disjoint pixel-clusters that, in the image, are within a neighborhood of the first respective non-disjoint pixel-cluster, (b) setting weights of connections of the graph according to a user-indicated classification in categories respectively associated with the terminals, and (c) segmenting the image into the categories by cutting the graph based upon the weights.

Abstract: A set of tensor-product B-Spline (TPB) basis functions is determined. A set of selected TPB prediction parameters to be used with the set of TPB basis functions for generating predicted image data in mapped images from source image data in source images of a source color grade is generated. The set of selected TPB prediction parameters is generated by minimizing differences between the predicted image data in the mapped images and reference image data in reference images of a reference color grade. The reference images correspond to the source images and depict same visual content as depicted by the source images. The set of selected TPB prediction parameters is encoded in a video signal as a part of image metadata along with the source image data in the source images. The mapped images are caused to be reconstructed and rendered with a recipient device of the video signal.

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: Backward reshaping metadata prediction models are trained with training SDR images and corresponding training HDR images. Content creation user input to define user adjusted HDR appearances for the corresponding training HDR images is received. Content-creation-user-specific modified backward reshaping metadata prediction models are generated based on the trained prediction models and the content creation user input. The content-creation-user-specific modified prediction models are used to predict operational parameter values of content-creation-user-specific backward reshaping mappings for backward reshaping SDR images into mapped HDR images of at least one content-creation-user-adjusted HDR appearance.