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: Inter-color image prediction is based on color grading modeling. Prediction is applied to the efficient coding of images and video signals of high dynamic range. Prediction models may include a color transformation matrix that models hue and saturation color changes and a non-linear function modeling color correction changes. Under the assumption that the color grading process uses a slope, offset, and power (SOP) operations, an example non linear prediction model is presented.

Abstract: Inter-color image prediction is based on color grading modeling. Prediction is applied to the efficient coding of images and video signals of high dynamic range. Prediction models may include a color transformation matrix that models hue and saturation color changes and a non-linear function modeling color correction changes. Under the assumption that the color grading process uses a slope, offset, and power (SOP) operations, an example non linear prediction model is presented.

Abstract: In layered Visual Dynamic range (VDR) coding, inter-layer prediction requires several color-format transformations between the input VDR and Standard Dynamic Range (SDR) signals. Coding and decoding architectures are presented wherein inter-layer prediction is performed in the SDR-based color format, thus reducing computational complexity in both the encoder and the decoder, without compromising coding efficiency or coding quality.

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: 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: Inter-color image prediction is based on color grading modeling. Prediction is applied to the efficient coding of images and video signals of high dynamic range. Prediction models may include a color transformation matrix that models hue and saturation color changes and a non-linear function modeling color correction changes. Under the assumption that the color grading process uses a slope, offset, and power (SOP) operations, an example non linear prediction model is presented.

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: 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 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: A unified media content directory may be created for multiple computing devices that store media content. These computing devices may be in the same network domain or span across different network domains. These computing devices may provide their media content through the unified media content directory based in part on standard technologies. A client that has a limited security permission may be able to access the unified media content directory and the media content identified in the unified media content directory in an intuitive, consistent manner, no matter where the client may be located, assuming the client has adequate digital rights for the media content the client. Additionally, load conditions of the media content servers may be monitored. A load balancing algorithm and high availability for accessing a piece of media content may be provided, if the media content can be accessed through more than one media content server.

Abstract: A method for transmitting data from a first device to a second device is provided. The method comprises steps of adding at least one NULL packet to the data in the first device to meet the alignment requirement of the second device and packing the data and the at least one NULL packet into a new packet; and transferring the new packet from the first device to the second device. And an apparatus for using the method is provided too.

Abstract: A system and method for efficiently performing an inverse telecine procedure includes an inverse telecine module that converts input frames of video information into corresponding output frames by applying an inverse telecine policy to the input frames. A motion statistics generator then calculates motion statistics results corresponding to the output frames. A synchronizer module then compares the motion statistics results to entries in a synchronization table for determining whether the inverse telecine procedure is correctly synchronized. The synchronizer module may then reposition a current start boundary of the inverse telecine procedure whenever the inverse telecine procedure is not correctly synchronized.

Abstract: A motion detection system can detect motion at a macroblock level of granularity and take an action based on the detection of motion or an event in a specified region of interest. The system comprises an ASIC capable of detecting an event in a macroblock of a frame of a video sequence, and an eventing engine for, responsive to the detection of the event by the ASIC, performing an action. Such a system can be configured by a user who provides an input specifying a region of interest on which motion detection should be performed by the motion detection system and a threshold value for determining whether or not motion has occurred in the region of interest.

Abstract: A system and method for efficiently performing an inverse telecine procedure includes an inverse telecine module that converts input frames of video information into corresponding output frames by applying an inverse telecine policy to the input frames. A motion statistics generator then calculates motion statistics results corresponding to the output frames. A synchronizer module then compares the motion statistics results to entries in a synchronization table for determining whether the inverse telecine procedure is correctly synchronized. The synchronizer module may then reposition a current start boundary of the inverse telecine procedure whenever the inverse telecine procedure is not correctly synchronized.