Abstract:
Compression transforming video into a compressed representation (which typically can be delivered at a capped pixel rate compatible with conventional video systems), including by generating spatially blended pixels and temporally blended pixels (e.g., temporally and spatially blended pixels) of the video, and determining a subset of the blended pixels for inclusion in the compressed representation including by assessing quality of reconstructed video determined from candidate sets of the blended pixels. Trade-offs may be made between temporal resolution and spatial resolution of regions of reconstructed video determined by the compressed representation to optimize perceived video quality while reducing the data rate. The compressed data may be packed into frames. A reconstruction method generates video from a compressed representation using metadata indicative of at least one reconstruction parameter for spatial regions of the reconstructed video.
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:
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 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:
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:
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:
Given an input progressive sequence, a video encoder creates a dual-layer stream that combines a backwards-compatible interlaced video stream layer with an enhancement layer to reconstruct full-resolution progressive video. Given two consecutive frames in the input progressive sequence, vertical processing generates a top field-bottom field (TFBF) frame in a base layer (BL) TFBF sequence, and horizontal processing generates a side-by-side (SBS) frame in an enhancement layer (EL) SBS video sequence. The BL TFBF and the EL SBS sequences are compressed together to create a coded, backwards compatible output stream.
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.