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.

Abstract: Provided is a non-stick cooking container, comprising a container body, in which the container body comprises a ribbed inner surface, the ribbed inner surface comprising a plurality of ribs and grooves arranged at regular intervals, a non-stick coating covering the surfaces of the ribs and the grooves, the ribs comprising a top surface, the grooves comprising a bottom surface. It is difficult to scratch or chip off the non-stick coating of the non-stick cooking container, which allows the cooking container to retain the non-stick properties over a long period.

Abstract: In an embodiment, a media source combines reference code values and mapping function parameters for mapping functions into video frames originally designated to carry pixel values. The video frames are delivered to a downstream device such as a media sink in an encoded video signal. The media sink extracts the mapping function parameters for the mapping functions from the encoded video signal and applies the mapping functions as a part of display management operations to map the reference code values to the mapped pixel values appropriate for the media sink. The mapped pixel values can be used to render images as represented by the reference code values.

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: An encoder receives an input enhanced dynamic range (EDR) image to be stored or transmitted using multiple coding formats in a layered representation. A layer decomposer generates a lower dynamic range (LDR) image from the EDR image. One or more base layer (BL) encoders encode the LDR image to generate a main coded BL stream and one or more secondary coded BL streams, where each secondary BL stream is coded in a different coding format than the main coded BL stream. A single enhancement layer (EL) coded stream and related metadata are generated using the main coded BL stream, the LDR image, and the input EDR image. An output coded stream includes the coded EL stream, the metadata, and either the main coded BL stream or one of the secondary coded BL streams. Computation-scalable decoding and display management processes for EDR images are also described.

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 layer. The encoder comprises a base layer quantizer (BLQ) and an enhancement layer quantizer (ELQ) and selects parameters of the BLQ and the ELQ by a joint BLQ-ELQ adaptation method which given a plurality of candidate sets of parameters for the BLQ, for each candidate set, computes a joint BLQ-ELQ distortion value based on a BLQ distortion function, an ELQ distortion function, and at least in part on the number of input pixels to be quantized by the ELQ. The encoder selects as the output BLQ parameter set the candidate set for which the computed joint BLQ-ELQ distortion value is the smallest. Example ELQ, BLQ, and joint BLQ-ELQ distortion functions are provided.

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.

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 a first image of a first spatial resolution and a second image of a second spatial resolution, wherein both the first image and the second image represent the same scene and the second spatial resolution is higher than the first spatial resolution. A filter is selected to up-sample the first image to a third image with a spatial resolution same as the second spatial resolution. The filtering coefficients for the up-sampling filter are computed by minimizing an error measurement (e.g., MSE) between pixel values of the second image and the third image. The computed set of filtering coefficients is signaled to a receiver (e.g., as metadata). A decoder receives the first image (or its approximation) and the metadata, and may up-sample the first image using the same filter and optimally selected filtering coefficients as those derived by the encoder.

Abstract: In layered VDR coding, inter-layer residuals are quantized by a non-linear quantizer before being coded by a subsequent encoder. Several non-linear quantizers are presented. Such non-linear quantizers may be based on sigmoid-like transfer functions, controlled by one or more free parameters that control their mid-range slope. These functions may also depend on an offset, an output range parameter, and the maximum absolute value of the input data. The quantizer parameters can time-vary and are signaled to a layered decoder. Example non-linear quantizers described herein may be based on the mu-law function, a sigmoid function, and/or a Laplacian distribution.

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: 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: 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: A sequence of visual dynamic range (VDR) images may be encoded using a standard dynamic range (SDR) base layer and one or more enhancement layers. A prediction image is generated by using piecewise cross-color channel prediction (PCCC), wherein a color channel in the SDR input may be segmented into two or more color channel segments and each segment is assigned its own cross-color channel predictor to derive a predicted output VDR image. PCCC prediction models may include first order, second order, or higher order parameters. Using a minimum mean-square error criterion, a closed form solution is presented for the prediction parameters for a second-order PCCC model. Algorithms for segmenting the color channels into multiple color channel segments are also presented.

Abstract: A sequence of visual dynamic range (VDR) images may be encoded using a standard dynamic range (SDR) base layer and one or more enhancement layers. A prediction image is generated by using piecewise cross-color channel prediction (PCCC), wherein a color channel in the SDR input may be segmented into two or more color channel segments and each segment is assigned its own cross-color channel predictor to derive a predicted output VDR image. PCCC prediction models may include first order, second order, or higher order parameters. Using a minimum mean-square error criterion, a closed form solution is presented for the prediction parameters for a second-order PCCC model. Algorithms for segmenting the color channels into multiple color channel segments are also presented.

Abstract: A visual dynamic range (VDR) coding system creates a sequence of VDR prediction images using corresponding standard dynamic range (SDR) images and a prediction function. For each prediction image, an encoder identifies one or more areas within the prediction image suitable for post-prediction filtering. For each identified post-prediction area, a post-prediction filtering mode is selected among one or more post-prediction filtering modes. The selected post-prediction filtering mode is applied to output a filtered prediction image. Information related to the post-prediction filtering areas and the selected corresponding post-prediction filtering modes may be communicated to a receiver (e.g., as metadata) for guided post-prediction filtering. Example post-prediction filtering modes that use low-pass averaging filtering or adaptive linear interpolation are also described.

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: An encoder receives a sequence of images in extended or visual dynamic range (VDR). For each image, a dynamic range compression function and associated parameters are selected to convert the input image into a second image with a lower dynamic range. Using the input image and the second image, a residual image is computed. The input VDR image sequence is coded using a layered codec that uses the second image as a base layer and a residual image that is derived from the input and second images as one or more residual layers. Using the residual image, a false contour detection method (FCD) estimates the number of potential perceptually visible false contours in the decoded VDR image and iteratively adjusts the dynamic range compression parameters to prevent or reduce the number of false contours. Examples that use a uniform dynamic range compression function are also described.

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 encoder receives a sequence of images in extended or visual dynamic range (VDR). For each image, a dynamic range compression function and associated parameters are selected to convert the input image into a second image with a lower dynamic range. Using the input image and the second image, a residual image is computed. The input VDR image sequence is coded using a layered codec that uses the second image as a base layer and a residual image that is derived from the input and second images as one or more residual layers. Using the residual image, a false contour detection method (FCD) estimates the number of potential perceptually visible false contours in the decoded VDR image and iteratively adjusts the dynamic range compression parameters to prevent or reduce the number of false contours. Examples that use a uniform dynamic range compression function are also described.