Abstract: A system and a method are disclosed for encoding data for transmission, including determining a rank of a first obtained symbol of the plurality of symbols, encoding, at an encoder, the rank of the first symbol, generating a new frequency entry for the first obtained symbol by incrementing an initial histogram frequency entry of the first obtained symbol, determining, based on the new frequency entry of the first obtained symbol, that the rank of the first obtained symbol of the plurality of symbols has a constraint violation with a rank of a first violating symbol in the first encoder LUT, swapping the rank of the first obtained symbol and the rank of the first violating symbol in the first encoder LUT so the constraint violation is resolved, and generating a compressed bit-stream by iteratively applying an encoding function to each symbol of the plurality of symbols.

Abstract: A forward reshaping mapping is generated to map a source image to a corresponding forward reshaped image of a lower dynamic range. The source image is spatially downsampled to generate a resized image into which noise is injected to generate a noise injected image. The forward reshaping mapping is applied to map the noise injected image to generate a noise embedded image of the lower dynamic range. A video signal is encoded with the noise embedded image and delivered to a recipient device for the recipient device to render a display image generated from the noise embedded image.

Abstract: Tensor-Product B-splines (TPB) have been shown to improve video quality when used to represent reshaping functions to map reshaped standard dynamic range content into high dynamic range (HDR) content; however, TPB prediction is computationally intensive and may not be supported by legacy devices. Methods and systems for backwards-compatible signaling of TPB-related metadata and a fast TPB prediction method are presented to overcome both of these limitations. Computation overhead for a TPB-based 3D look-up table is reduced by using temporary two-dimensional arrays. A remapping of the most significant bits of a legacy bit-depth parameter allows for backwards compatibility.

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: A method may include receiving symbol probabilities from a dataset, and computing a group probability for each group of symbols in a first codebook based on the received symbol probabilities. The method may further include determining that a first group probability of a first group in the first codebook is lower than a second group probability of a second group in the first codebook, swapping a first prefix corresponding to the first group with a second prefix corresponding to the second group in response, and storing the first prefix corresponding to the second group and the second prefix corresponding to the first group in a second codebook.

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 method may include receiving a first symbol, and encoding the first symbol based on an initial codebook including a symbol frequency and a ranking for each symbol, and a group frequency for each group of symbols. The method may include incrementing a symbol frequency of the first symbol based on receiving the first symbol, swapping a rank of a lowest ranking symbol from among symbols in the initial codebook that have a symbol frequency lower than the incremented symbol frequency of the first symbol with a rank of the first symbol, in response to the symbol frequency of the lowest ranking symbol being lower than the incremented symbol frequency of the first symbol, and storing an updated codebook in a memory accessible by an encoder and/or a decoder.

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: 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: 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: 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: 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: A system and method for encoding. In some embodiments, the method includes: encoding a first pixel of an image using a first codec; selecting, based on a remaining bit budget, a second codec; encoding a second pixel, immediately following the first pixel, using the second codec, wherein: the first codec has a first loss, according to a measure of loss; and the second codec has a second loss, according to the measure of loss, the second loss being greater than zero and less than the first loss.

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: A first reshaping mapping is performed on a first image represented in a first domain to generate a second image represented in a second domain. The first domain is of a first dynamic range different from a second dynamic range of which the second domain is. A second reshaping mapping is performed on the second image represented in the second domain to generate a third image represented in the first domain. The third image is perceptually different from the first image in at least one of: global contrast, global saturation, local contrast, local saturation, etc. A display image is derived from the third image and rendered on a display device.

Abstract: A system and a method are disclosed for encoding data for transmission, including determining a rank of a first obtained symbol of the plurality of symbols, encoding, at an encoder, the rank of the first symbol, generating a new frequency entry for the first obtained symbol by incrementing an initial histogram frequency entry of the first obtained symbol, determining, based on the new frequency entry of the first obtained symbol, that the rank of the first obtained symbol of the plurality of symbols has a constraint violation with a rank of a first violating symbol in the first encoder LUT, swapping the rank of the first obtained symbol and the rank of the first violating symbol in the first encoder LUT so the constraint violation is resolved, and generating a compressed bit-stream by iteratively applying an encoding function to each symbol of the plurality of symbols.