Abstract:
Systems, apparatus, articles, and methods are described including operations to generate a weighted look-up-table based at least in part on individual pixel input values within an active block region and on a plurality of contrast compensation functions. A second level compensation may be performed for a center pixel block of the active region based at least in part on the weighted look-up-table.
Abstract:
Systems, devices and methods are described including performing scalable video coding using inter-layer residual prediction, inter-layer residual prediction in an enhancement layer coding unit, prediction unit, or transform unit may use residual data obtained from a base layer or from a lower enhancement layer. The residual may be subjected to upsample filtering and/or refinement filtering. The upsample or refinement filter coefficients may be predetermined or may be adoptively determined.
Abstract:
According to one embodiment, a method is disclosed. The method includes performing a local content analysis on video data to classify pixels into singular pixels, motion pixels and static pixels.
Abstract:
Systems, apparatus and methods are described including determining a prediction residual for a channel of video data; and determining, using the first channel's prediction residual, a prediction residual for a second channel of the video data. Further, a prediction residual for a third channel of the video data may be determined using the second channel's prediction residual.
Abstract:
Reconstructed picture quality for a video codec system may be improved by categorizing reconstructed pixels into different histogram bins with histogram segmentation and then applying different filters on different bins. Histogram segmentation may be performed by averagely dividing the histogram into M bins or adaptively dividing the histogram into N bins based on the histogram characteristics. Here M and N may be a predefined, fixed, non-negative integer value or an adaptively generated value at encoder side and may be sent to decoder through the coded bitstream.
Abstract:
Techniques are disclosed involving contrast adjustment for images. For example, an input image is classified based on its pixel value characteristics, as expressed in an input brightness histogram. From such a classification, a target histogram distribution for a corresponding output image (i.e., a contrast-adjusted transformation of the input image) may be specified. With the target histogram of the output image specified, a transformation function may be derived that maps input image values to output image values. Moreover, transitions of such transformation functions may be smoothed. Such smoothing may provide advantages, such as a reduction in flickering associated with video data.
Abstract:
According to one embodiment, a method is disclosed. The method includes receiving video data performing pre-filtering on the data, performing content analysis is applied to identify an area of the data, applying a two-dimensional (2-D) 2nd gradient operation to extract a high frequency component and normalizing the high frequency component related to high frequency information from a previous picture.
Abstract:
Methods and systems to apply motion estimation (ME) based on reconstructed reference pictures in a B frame or in a P frame at a video decoder. For a P frame, projective ME may be performed to obtain a motion vector (MV) for a current input block. In a B frame, both projective ME and mirror ME may be performed to obtain an MV for the current input block. The ME process can be performed on sub-partitions of the input block, which may reduce the prediction error without increasing the amount of MV information in the bitstream. Decoder-side ME can be applied for the prediction of existing inter frame coding modes, and traditional ME or the decoder-side ME can be adaptively selected to predict a coding mode based on a rate distribution optimization (RDO) criterion.
Abstract:
Techniques are described that can be used to apply motion estimation (ME) based on reconstructed reference pictures in a B frame or in a P frame at a video decoder. For a P frame, projective ME may be performed to obtain a motion vector (MV) for a current input block. In a B frame, both projective ME and mirror ME may be performed to obtain an MV for the current input block. A metric an be used determining a metric for each pair of MV0 and MV1 that is found in the search path, where the metric is based on a combination of a first, second, and third metrics. The first metric is based on temporal frame correlation, a second metric is based on spatial neighbors of the reference blocks, and a third metric is based on the spatial neighbors of the current block.
Abstract:
Techniques are described that can be used to determine parameters of an adaptive Wiener filter to apply to a video region. The following parameters of the Wiener filter may be adjusted: coefficients, coefficient quantization, filter type, filter size, prediction mode, entropy encoding, and number of filter tables. The parameters associated with the lowest rate distortion cost of the encoder are selected for transmission with the encoded video. If not using adaptive Wiener filtering results in a lowest rate distortion cost, then adaptive Wiener filtering is not used for the video region. If using adaptive Wiener filtering results in a lowest rate distortion cost, then the parameters applied by the adaptive Wiener filtering that result in the lowest rate distortion cost are communicated with the filtered video region.