Abstract: A two-stage context adaptive binary arithmetic coding (CABAC) parser is provided to efficiently transcode an input video bitstream that is partitioned into tiles into a non-tiled based video bitstream. A picture of the input video bitstream is partitioned into one or more tiles, each of which has multiple coding tree units (CTUs) according to the HEVC standard. The two-stage CABAC parser parses the input video bitstream in tile scan order in the first stage and generates a list of identified CTUs, whose CABAC state data are saved for the second stage parsing. In the second stage parsing, the two-stage parser parses the same input video bitstream in raster scan order using the saved CABAC state data of the identified CTUs.

Abstract: A two-stage context adaptive binary arithmetic coding (CABAC) parser is provided to efficiently transcode an input video bitstream that is partitioned into tiles into a non-tiled based video bitstream. A picture of the input video bitstream is partitioned into one or more tiles, each of which has multiple coding tree units (CTUs) according to the HEVC standard. The two-stage CABAC parser parses the input video bitstream in tile scan order in the first stage and generates a list of identified CTUs, whose CABAC state data are saved for the second stage parsing. In the second stage parsing, the two-stage parser parses the same input video bitstream in raster scan order using the saved CABAC state data of the identified CTUs.

Abstract: A system (and a method) are disclosed for adaptively selecting quantization parameter for each region of input video signal to be encoded within a video processing system. The system includes a frame partition module, an edge feature detector, a macroblock adaptive quantization energy (AQEnergy) evaluator and a macroblock adaptive quantization parameter selector. The frame partition module partitions a frame of an input video signal into smaller blocks of pixel data. The edge feature detector generates an edge direction histogram for each block to be encoded. The macroblock AQEnergy evaluator receives the edge direction histogram of the block, calculates the AQEnergy of the block and generates the adaptive quantization score (AQScore) of the macroblock. The macroblock adaptive quantization parameter selector selects an appropriate macroblock quantization parameter corresponding to the macroblock AQScore by a combination of programmable scaling and threshold logic.

Abstract: Embodiments of noise reduction systems and methods are disclosed. One method embodiment, among others, comprises transforming a residual signal to produce transform coefficients, and applying the transform coefficients to a quantization matrix and a configurable gain matrix to provide a frequency-selective weighting of the transform coefficients having a gain that is sensitive to noise levels.

Abstract: A high definition digital video presentation system is provided with an interpolator which upsamples standard resolution MPEG pictures to higher resolution, preferably to double the number of pixels in both the vertical and horizontal dimensions. The upsampling is performed after the decoding and transformation of the incoming picture and prior to the buffering of the picture data or the performance of motion compensation by which pixel data are copied from previously received pictures. In the preferred embodiment, frame pictures are decoded, upsampled and stored in full frame picture buffers, preferably, in two buffers, one to be copied into each field of subsequent pictures in the performance of motion compensation. Interpolation may be by frame, where intervening lines of pixels are interpolated from the pixels of adjacent odd and even lines, and by field, where an intervening odd (or even) line of pixels is interpolated from the pixels of each pair of adjacent even (or odd) lines.

Abstract: A nonlinear video filter which provides an output of increased sharpness with reduced artifacts as compared to prior art filters. A “pivot” value is identified at a pixel based on the value of pixels neighboring that pixel. Then, a new value for the pixel is computed by adding to the pivot value, an amount based on the difference between the original pixel value and the pivot value. The pivot value may be computed as the average of the original values for a number, e.g., 2n, neighboring pixels, or as the average of the maximum and minimum original pixel values among the 2n neighboring pixels. The difference between the original pixel value and the pivot value is multiplied by a factor k, and then added to the pivot value. For computational simplicity, the factor k is selected to be a power of two. Filtering for k=2, k=4 and k=16 are illustrated. The new value is limited to the maximum and minimum original pixel values among the 2n original pixel values to avoid overshoot.