Abstract: A sequence of visual dynamic range (VDR) images is encoded using a standard dynamic range (SDR) base layer and one or more enhancement layers. A predicted VDR image is generated from an SDR input by using a weighted, multi-band, cross-color channel prediction model. Exponential weights with an adaptable decay parameter for each band are also presented.

Abstract: An encoder receives one or more input pictures of enhanced dynamic range (EDR) to be encoded in a coded bit stream comprising a base layer and one or more enhancement layers. To encode the chroma pixels, the encoder generates a luma mask and a corresponding chroma mask. Based on generated high-clipping and low-clipping thresholds, the encoder determines the appropriate parameters to encode the chroma values in the base and enhancement layers.

Abstract: Inter-color image prediction is based on multi-channel multiple regression (MMR) models. Image prediction is applied to the efficient coding of images and video signals of high dynamic range. MMR models may include first order parameters, second order parameters, and cross-pixel parameters. MMR models using extension parameters incorporating neighbor pixel relations are also presented. Using minimum means-square error criteria, closed form solutions for the prediction parameters are presented for a variety of MMR models.

Abstract: In an embodiment, a control map of false contour filtering is generated for a predicted image. The predicted image is predicted from a low dynamic range image mapped from the wide dynamic range image. Based at least in part on the control map of false contour filtering and the predicted image, one or more filter parameters for a sparse finite-impulse-response (FIR) filter are determined. The sparse FIR filter is applied to filter pixel values in a portion of the predicted image based at least in part on the control map of false contour filtering. The control map of false contour filtering is encoded into a part of a multi-layer video signal that includes the low dynamic range image.

Abstract: Inter-color image prediction is based on multi-channel multiple regression (MMR) models. Image prediction is applied to the efficient coding of images and video signals of high dynamic range. MMR models may include first order parameters, second order parameters, and cross-pixel parameters. MMR models using extension parameters incorporating neighbor pixel relations are also presented. Using minimum means-square error criteria, closed form solutions for the prediction parameters are presented for a variety of MMR models.

Abstract: Coding syntaxes in compliance with same or different VDR specifications may be signaled by upstream coding devices such as VDR encoders to downstream coding devices such as VDR decoders in a common vehicle in the form of RPU data units. VDR coding operations and operational parameters may be specified as sequence level, frame level, or partition level syntax elements in a coding syntax. Syntax elements in a coding syntax may be coded directly in one or more current RPU data units under a current RPU ID, predicted from other partitions/segments/ranges previously sent with the same current RPU ID, or predicted from other frame level or sequence level syntax elements previously sent with a previous RPU ID. A downstream device may perform decoding operations on multi-layered input image data based on received coding syntaxes to construct VDR images.

Abstract: Error control in multi-stream visual dynamic range (VDR) codecs is described, including for a case of a layer-decomposed (non-backward compatible) video codecs. Error control can be provided by concealing lost and/or corrupted data in data frames of a decoded VDR bitstream prior to rendering a corresponding VDR image. Various algorithms and methods for concealing lost and/or corrupted data are provided.

Abstract: Methods and systems for generating and applying scene-stable metadata for a video data stream are disclosed herein. A video data stream is divided or partitioned into scenes and a first set of metadata may be generated for a given scene of video data. The first set of metadata may be any known metadata as a desired function of video content (e.g., luminance). The first set of metadata may be generated on a frame-by-frame basis. In one example, scene-stable metadata may be generated that may be different from the first set of metadata for the scene. The scene-stable metadata may be generated by monitoring a desired feature with the scene and may be used to keep the desired feature within an acceptable range of values. This may help to avoid noticeable and possibly objectionably visual artifacts upon rendering the video data.

Abstract: Methods and systems for generating and applying scene-stable metadata for a video data stream are disclosed herein. A video data stream is divided or partitioned into scenes and a first set of metadata may be generated for a given scene of video data. The first set of metadata may be any known metadata as a desired function of video content (e.g., luminance). The first set of metadata may be generated on a frame-by-frame basis. In one example, scene-stable metadata may be generated that may be different from the first set of metadata for the scene. The scene-stable metadata may be generated by monitoring a desired feature with the scene and may be used to keep the desired feature within an acceptable range of values. This may help to avoid noticeable and possibly objectionably visual artifacts upon rendering the video data.

Abstract: A sequence of visual dynamic range (VDR) images is encoded using a standard dynamic range (SDR) base layer and one or more enhancement layers. A predicted VDR image is generated from an SDR input by using a weighted, multi-band, cross-color channel prediction model. Exponential weights with an adaptable decay parameter for each band are also presented.

Abstract: Techniques use multiple lower bit depth (e.g., 8 bits) codecs to provide higher bit depth (e.g., 12+ bits) high dynamic range images from an upstream device to a downstream device. Multiple layers comprising a base layer and one or more enhancement layers may be used to carry video signals comprising image data compressed by lower bit depth encoders to a downstream device, wherein the base layer cannot be decoded and viewed on its own. Lower bit depth input image data to base layer processing may be generated from higher bit depth high dynamic range input image data via advanced quantization to minimize the volume of image data to be carried by enhancement layer video signals. The image data in the enhancement layer video signals may comprise residual values, quantization parameters, and mapping parameters based in part on a prediction method corresponding to a specific method used in the advanced quantization.

Abstract: Novel methods and systems for decoding and displaying enhanced dynamic range (EDR) video signals are disclosed. To accommodate legacy digital media players with constrained computational resources, compositing and display management (DM) operations are moved from a digital media player to its attached EDR display. On a video receiver, base and enhancement video layers are decoded and multiplexed together with overlay graphics into an interleaved stream. The video and graphics signals are all converted to a common format which allows metadata to be embedded in the interleaved signal as part of the least significant bits in the chroma channels. On the display, the video and the graphics are de-interleaved. After compositing and display management operations guided by the received metadata, the received graphics data are blended with the output of the DM process and the final video output is displayed on the display's panel.

Abstract: A sequence of visual dynamic range (VDR) images is encoded using a standard dynamic range (SDR) base layer and one or more enhancement layers. A predicted VDR image is generated from an SDR input by using a weighted, multi-band, cross-color channel prediction model. Exponential weights with an adaptable decay parameter for each band are also presented.

Abstract: Techniques use multiple lower bit depth codecs to provide higher bit depth, high dynamic range, images from an upstream device to a downstream device. A base layer and one or more enhancement layers may be used to carry video signals, wherein the base layer cannot be decoded and viewed on its own. Lower bit depth input image data to base layer processing may be generated from higher bit depth high dynamic range input image data via advanced quantization to minimize the volume of image data to be carried by enhancement layer video signals. The image data in the enhancement layer video signals may comprise residual values, quantization parameters, and mapping parameters based in part on a prediction method corresponding to a specific method used in the advanced quantization. Adaptive dynamic range adaptation techniques take into consideration special transition effects, such as fade-in and fade-outs, for improved coding performance.

Abstract: Inter-color image prediction is based on multi-channel multiple regression (MMR) models. Image prediction is applied to the efficient coding of images and video signals of high dynamic range. MMR models may include first order parameters, second order parameters, and cross-pixel parameters. MMR models using extension parameters incorporating neighbor pixel relations are also presented. Using minimum means-square error criteria, closed form solutions for the prediction parameters are presented for a variety of MMR models.

Abstract: Methods and systems for generating and applying scene-stable metadata for a video data stream are disclosed herein. A video data stream is divided or partitioned into scenes and a first set of metadata may be generated for a given scene of video data. The first set of metadata may be any known metadata as a desired function of video content (e.g., luminance). The first set of metadata may be generated on a frame-by-frame basis. In one example, scene-stable metadata may be generated that may be different from the first set of metadata for the scene. The scene-stable metadata may be generated by monitoring a desired feature with the scene and may be used to keep the desired feature within an acceptable range of values. This may help to avoid noticeable and possibly objectionably visual artifacts upon rendering the video data.

Abstract: In an embodiment, a source video signal comprising reference code values and mapping function parameters for one or more mapping functions to map the reference code values to device-specific pixel values. The reference code values and the mapping function parameters are combined into first video frames in a first video signal format. The mapping function parameters represent DM metadata carried in the first video frames. Second video frames in a second video signal format are generated based on the first video frames in the first video signal format and a mapping between the first video signal format and the second video signal format. The second video frames are sent to a video sink device through the video link in an encoded video signal of the second video signal format.

Abstract: Inter-color image prediction is based on multi-channel multiple regression (MMR) models. Image prediction is applied to the efficient coding of images and video signals of high dynamic range. MMR models may include first order parameters, second order parameters, and crosspixel parameters. MMR models using extension parameters incorporating neighbor pixel relations are also presented. Using minimum means-square error criteria, closed form solutions for the prediction parameters are presented for a variety of MMR models.

Abstract: An input image is divided into non-overlapping regions. For each of the non-overlapping regions, first output data is predicted with a first prediction function, parameters related thereto and region-specific input image data. For each region with prior-predicted neighbor regions, a pixel border portion, adjacent to the neighbor region, is defined. For the pixels in the defined border portion, second output data is predicted with a second prediction function, parameters related thereto, input image data from the border portion of the current region, and input prediction parameter data from the neighbor region. The first output prediction data is fused with the second output data to predict a final set of output prediction values.

Abstract: An encoder receives a target image in a standard dynamic range and a guide image in a high dynamic range, wherein both the target image and the guide image represent the same scene. A color transient improvement (CTI) filter is selected to predict a chroma component of a decoded version of the target image based on both the luma and chroma components of the target image and the guide image. The filtering coefficients for the CTI filter are computed by minimizing an error measurement (e.g., MSE) between pixel values of the decoded image and the guide image. The computed set of filtering coefficients is signaled to a receiver (e.g., as metadata). A decoder receives the coded image and the metadata, and applies the same CTI filter to the decoded image to generate an output image.