Abstract: The disclosure relates to tuning configuration parameters for graphics pipeline for better user experience. A device for graphics processing, comprising: hardware engines; a graphics pipeline at least partly implemented by the hardware engines; and a tuner, coupled to the hardware engines and the graphics pipeline, the tuner to: collect statuses of the device during runtime for a previous frame; determine configuration parameters based on the collected statuses, the configuration parameters associated with three-dimensional 3D rendering, pre-processing and video encoding of the graphics pipeline; and tune the graphics pipeline with the determined configuration parameters for processing a next frame.

Abstract: Methods, articles, and systems of image processing comprise obtaining image data of frames of a video sequence. The method also includes determining multiple reference frames of a current frame in the video sequence. The multiple reference frames each have at least one motion compensated (MC) block of image data. Also, the method then includes generating a weight that factors noise, distortion variance, and dispersion distribution between the same MC block position and the current block. Thereafter, the method includes generating denoised filtered image data comprising applying one of the weights to the image data of the motion compensated (MC) block.

Abstract: Techniques related to accelerated video enhancement using deep learning selectively applied based on video codec information are discussed. Such techniques include applying a deep learning video enhancement network selectively to decoded non-skip blocks that are in low quantization parameter frames, bypassing the deep learning network for decoded skip blocks in low quantization parameter frames, and applying non-deep learning video enhancement to high quantization parameter frames.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed. Example apparatus disclosed herein are to process features extracted from first and second downscaled image frames to determine block classifications for respective blocks of the first and the second downscaled image frames. Disclosed example apparatus are also to generate a map based on the block classifications, the map including values representative of amounts of change associated with blocks of the second downscaled image frame and corresponding blocks of the first downscaled image frame. Disclosed example apparatus are further to adjust a quantization parameter of a full-scale image frame based on the map, the full-scale image frame corresponding to the at least one of the first or the second downscaled image frames.

Abstract: Techniques related to adaptive quantization matrix selection using machine learning for video coding are discussed. Such techniques include applying a machine learning model to generate an estimated quantization parameter for a frame and selecting a set of quantization matrices for encode of the frame from a number of sets of quantization matrices based on the estimated quantization parameter.

Abstract: The present disclosure provides the use of a fluorescent imaging plate reader (FLIPR) high-throughput real-time fluorescence detection and analysis system in detection of calcium signals in plants, which successfully applies the FLIPR to the detection of calcium signals in plants, and increases the use of the FLIPR in the detection of calcium signals in plants. In addition, a method for detecting calcium signals in plants based on FLIPR provided by the present disclosure detects changes in calcium signals generated by stimulation of plants by an exogenous calcium signal CaCl2 solution, which is the basis of high-throughput real-time fluorescence detection of calcium ions in plants.

Abstract: Techniques related to coding video using adaptive quantization rounding offsets for use in transform coefficient quantization are discussed. Such techniques may include determining the value of a quantization rounding offset for a picture of a video sequence based on evaluating a maximum coding bit limit of the picture, a quantization parameter of the picture, and parameters corresponding to the video.

Abstract: An example apparatus for encoding video frames includes a frame analyzer to execute a look ahead analysis on a received set of frames. The frame analyzer includes a look ahead video analyzer to down-sample the set of frames and encode the down-sampled frames with a constant quantization parameter (QP). A number of generated bits for each of the frames is used as a complexity measurement for each of the frames. The apparatus further includes an encoder to encode the input frame using an adjusted bit allocation based on a relative complexity of the input frame in relation to a complexity of the set of frames.

Abstract: Embodiments are generally directed to transport controlled video coding. An embodiment of an apparatus includes one or more processors to process data; a memory to store data, including data for video streaming; and a video processing mechanism including an encoder and a transport mechanism, wherein the video processing mechanism is to generate a prediction of channel throughput for a network channel, encode one or more bitstreams based on the prediction, including encoding a plurality of bitstreams including a first bitstream and a second bitstream if the prediction indicates an increase or decrease in channel throughput and encoding a single bitstream if the prediction indicates a stable channel throughput; and select a bitstream of the one or more bitstreams for a current frame.

Abstract: Example methods, apparatus, systems and articles of manufacture to implement adaptive loop filter classification and selection for video coding are disclosed. Examples disclosed herein determine whether a collection of available adaptive loop filter sets associated with luma components of the input picture is empty. When the collection of available adaptive loop filter sets is not empty, disclosed examples also enable adaptive loop filtering for the luma components of the input picture, and select at least one of the collection of available adaptive loop filter sets to include in a selection of adaptive loop filter sets for the input picture, with the selection based on an order in which ones of the available adaptive loop filter sets in the collection were derived. Some disclosed examples additionally or alternatively perform block classification to determine accumulated class statistics for derivation of an adaptive loop filter set associated with the input picture.

Abstract: An example apparatus for adaptively encoding video frames includes a network analyzer to predict an instant bitrate based on channel throughput feedback received from a network. The apparatus also includes a content analyzer to generate ladder info based on a received frame. The apparatus further includes an adaptive decision executer to determine a frame rate, a video resolution, and a target frame size based on the predicted instant bitrate and the ladder outputs. The apparatus further includes an encoder to encode the frame based on the frame rate, the video resolution, and the target frame size.

Abstract: Techniques related to selecting restoration filter coefficients for 2-dimensional loop restoration filters for super resolution video coding are discussed. Such techniques include upscaling reconstructed video frames along only a first dimension and selecting filter coefficients for portions of the frame by an evaluation that, for each pixel of the portion, uses only pixel values that are aligned with the first dimension. Selection of filter coefficients for the second dimension may be skipped or made using only a subset of available filter coefficients.

Abstract: Techniques related to coding video using adaptive quantization rounding offsets for use in transform coefficient quantization are discussed. Such techniques may include determining the value of a quantization rounding offset for a picture of a video sequence based on evaluating a maximum coding bit limit of the picture, a quantization parameter of the picture, and parameters corresponding to the video.

Abstract: Systems and methods for detecting screen contents and adaptive enablement of screen content coding modes. Encoding mode decision may be made adaptive to include or exclude screen content coding (SCC) modes. In some embodiments, a screen content decision is based on one or more statistics characterizing a distribution of meaningful colors (e.g., chroma) and/or intensities (e.g., luma) determined for a population of pixels of an input picture. In some embodiments, a screen content decision is based on one or more statistics characterizing the pure flat area of an input picture and the area with extreme sharp edges. Pictures may be encoded according to a mode selection that is adaptive to the screen content decision, for example selecting between encoding modes that include SCC modes, or selecting between encoding modes that exclude SCC modes.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed. Example apparatus disclosed herein are to process features extracted from first and second downscaled image frames to determine block classifications for respective blocks of the first and the second downscaled image frames. Disclosed example apparatus are also to generate a map based on the block classifications, the map including values representative of amounts of change associated with blocks of the second downscaled image frame and corresponding blocks of the first downscaled image frame. Disclosed example apparatus are further to adjust a quantization parameter of a full-scale image frame based on the map, the full-scale image frame corresponding to the at least one of the first or the second downscaled image frames.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to improve video encoding. An example apparatus includes at least one memory, instructions, and processor circuitry to at least one of execute or instantiate the instructions to identify a first video frame as a critical video frame with respect to a previous video frame, generate filter coefficients of a video filter based on pixel data of the first video frame or pixel data of a previous critical video frame, and encode the first video frame with the filter coefficients.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to improve video encoding. An example apparatus includes at least one memory, instructions, and processor circuitry to generate a pool of clipping index set candidates by executing a machine learning model, select a clipping index set from the pool of the clipping index set candidates based on a rate distortion cost associated with the clipping index set, the clipping index set including clipping coefficients, and filter a video frame based on the clipping coefficients.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to encode and decode video using quantization matrices. An example apparatus includes interface circuitry to access an input frame of video, quantization matrix syntax encoder circuitry to encode a set of user-defined quantization matrices into a sequence header associated with a sequence of video frames including the input frame, adaptive quantization matrix selector circuitry to select a subset of quantization matrices from a combination of a set of default quantization matrices and the set of user-defined quantization matrices, adaptive segment selector circuitry to select a first one of the subset of quantization matrices for a first segment of the input frame, the input frame to be divided into a plurality of segments including the first segment, and encoder circuitry to quantize transform coefficients of the first segment of the input frame based on the first one of the subset of quantization matrices.

Abstract: An embodiment may include a display processor, memory to store a 2D frame corresponding to a projection from a 360 video, and a quality selector to select a quality factor for a block of the 2D frame based on quality information from neighboring blocks of the 2D frame, including blocks which are neighboring only in the 360 video space. The system may also include a range adjuster to adjust a search range for the 2D frame based on a search area of the 2D frame, a viewport manager to determine if a request for a viewport of the 2D frame extends beyond a first edge of the 2D frame and to fill the requested viewport with wrap-around image information, and/or a motion estimator to estimate motion information based on both color information and depth information. Other embodiments are disclosed and claimed.

Abstract: Techniques related to video coding include multi-layer video coding with content-sensitive cross-layer reference frame re-assignment.