Abstract: Guided filtering is applied, with a camera raw image as a guidance image, to a first image to generate an intermediate image. A dynamic range mapping is performed on the intermediate image to generate a second image of a different dynamic range. The second image is used to generate specific local reshaping function index values for selecting specific local reshaping functions. The specific local reshaping functions are applied to the second image to generate a locally reshaped image.

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.

Abstract: An input image of a first bit depth in an input domain is received. Forward reshaping operations are performed on the input image to generate a forward reshaped image of a second bit depth in a reshaping domain. An image container containing image data derived from the forward reshaped image is encoded into an output video signal of the second bit depth.

Abstract: Novel methods and systems are described for providing interactive motion blur on an image by motion inputs from movements of the mobile device displaying the image. The device can process the motion blur by modules providing motion blur parameter estimation, blur application, and image composition based on metadata and a baseline image from the encoder. A pre-loaded filter bank can provide blur kernels for blur application.

Abstract: In a cloud-based system for encoding high dynamic range (HDR) video, each node receives a video segment and bumper frames. Each segment is subdivided into primary scenes and secondary scenes to derive scene-based forward reshaping functions that minimize the amount of reshaping-related metadata when coding the video segment. When a parent scene of a secondary scene is processed by two or more neighboring nodes, initial forward reshaping functions and trim-pass correction parameters are adjusted using reference tone-mapping functions and updated scene-based trim-pass correction parameters.

Abstract: Methods, systems, and bitstream syntax are described for metadata signaling and film-grain parameter adaptation based on a viewing environment which may differ from a reference environment. Example adaptation models are provided for viewing parameters that include: ambient room illumination, viewing distance, and pixels per inch in a target display. Example systems include a single reference viewing environment model and a multi-reference viewing environment model supporting adaptation of film-grain model parameters via adaptation functions or interpolation.

Abstract: A global index value is generated for selecting a global reshaping function for an input image of a relatively low dynamic range using luma codewords in the input image. Image filtering is applied to the input image to generate a filtered image. The filtered values of the filtered image provide a measure of local brightness levels in the input image. Local index values are generated for selecting specific local reshaping functions for the input image using the global index value and the filtered values of the filtered image. A reshaped image of a relatively high dynamic range is generated by reshaping the input image with the specific local reshaping functions selected using the local index values.

Abstract: In a cloud-based system for encoding high dynamic range (HDR) video, each node receives a video segment and bumper frames. Each segment is subdivided into primary scenes and secondary scenes to derive scene-based forward reshaping functions that minimize the amount of reshaping-related metadata when coding the video segment, while maintaining temporal continuity among scenes processed by multiple 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: Embodiments described herein provide a unified container format for delivering different multimedia applications. One embodiment provides a data structure utilized for implementing a plurality of multimedia applications. The data structure includes a first metadata level including low-level metadata used to perform operations associated with media data in a bitstream. The data structure includes a second metadata level including mid-level metadata used to apply operation metadata to render the media data. The data structure includes a third metadata level including upper-level metadata used to utilize the low-level metadata and the mid-level metadata to deliver the plurality of multimedia applications.

Abstract: Methods and corresponding systems to process face regions are disclosed. The described methods include providing face bounding boxes and confidence levels for the faces, generating a histogram of the pixels and the faces, generating a probability of face, and generating a face probability map. A face contrast adjustment and a face saturation adjustment can be applied to the face probability map.

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 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: An input image represented in an input domain is received from an input video signal. Forward reshaping is performed on the input image to generate a forward reshaped image represented in a reshaped image domain. Non-reshaping encoding operations are performed to encode the reshaped image into an encoded video signal. At least one of the non-reshaping encoding operations is implemented with an ML model that has been previously trained with training images in one or more training datasets in a preceding training stage. A recipient device of the encoded video signal is caused to generate a reconstructed image from the forward reshaped image.

Abstract: Input images are received as input to a multi-node system. The input images are divided into segments assigned to respective nodes of the multi-node system. Primary and secondary scenes are identified in the segments to ensure compliance with minimum and average distance constraints. Scene-level forward reshaping mappings are generated for the scenes by a respective node for an assigned segment. Forward reshaped images in the segment are generated by the node using the forward reshaping mappings and encoded into an output video signal, which enables a recipient device to generate reconstructed images and to render display images derived from the reconstructed images on an image display.

Abstract: A method, for generating (a) a forward reshaping function for compressing an input high-dynamic range (HDR) image into a reshaped standard-dynamic-range (SDR) image and (b) a backward reshaping function for decompressing the reshaped SDR image into a reconstructed HDR image, includes (i) optimizing the forward reshaping function to minimize a deviation between the reshaped SDR image and an input SDR image corresponding to the input HDR image, (ii) optimizing the backward reshaping function to minimize a deviation between the reconstructed HDR image and the input HDR image, and (iii) until a termination condition is met, applying a correction to the input SDR image and reiterating, based on the input SDR image as corrected, the steps of optimizing the forward and backward reshaping functions.

Abstract: Input images are received as input to a multi-node system. The input images are divided into segments assigned to respective nodes of the multi-node system. Primary and secondary scenes are identified in the segments to ensure compliance with minimum and average distance constraints. Scene-level forward reshaping mappings are generated for the scenes by a respective node for an assigned segment. Forward reshaped images in the segment are generated by the node using the forward reshaping mappings and encoded into an output video signal, which enables a recipient device to generate reconstructed images and to render display images derived from the reconstructed images on an image display.

Abstract: An input image to a pipeline of chained reshaping functions is received. Reference images are generated from the input image. The input image and the reference images are used to determine operational parameters for chained reshaping functions in the pipeline of chained reshaping functions. A reshaped image generated from one or more of the chained reshaping functions is encoded in a video signal along with image metadata. The image metadata includes some or all of the operational parameters specifying the chained reshaping functions. A recipient device of the video signal is caused to use the image metadata and the reshaped image to generate a reconstructed image.

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 apparatus for transmission of volumetric images in the MPI format. According to an example embodiment, texture and alpha layers of multiplane images are packed, as tiles, into a sequence of video frames. The sequence of video frames is then compressed to generate a video bitstream, which is transmitted together with a metadata bitstream specifying at least the parameters of the packing arrangement for the tiles in the sequence of video frames. Example packing arrangements include various selectable spatial and temporal arrangements for texture layers, alpha layers, and camera views. In some examples, the metadata bitstream is implemented using a SEI message and includes parameters selected from the group consisting of a size of the reference view, the number of layers in the multiplane image, the number of simultaneous views, one or more characteristics of the packing arrangement, layer merging information, dynamic range adjustment information, and reference view information.

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.