Abstract:
Methods, systems, and computer programs for encoding and decoding image are described. In some aspects, an input data block and a prediction data block are accessed. A projection factor is generated based on a projection of the input data block onto the prediction data block. A scaled prediction data block is generated by multiplying the projection factor by the prediction data block. A residual data block is generated based on a difference between the input data block and the scaled prediction data block. In some aspects, a prediction data block, a residual data block, and a projection factor associated with the residual data block are accessed. A scaled prediction data block is generated by multiplying the projection factor by the prediction data block. An output data block is generated by summing the residual data block and the scaled prediction data block.
Abstract:
Encoding and decoding methods are presented that used offset-based adaptive reconstruction levels. The offset data is inserted in the bitstream with the encoded video data. The offset data may be differential data and may be an index to an array of offset values from which the differential offset is calculated by the decoder. The offset to an adaptive reconstruction level may be adjusted for each slice. The offsets may be specific to a particular level/index and data type. In some cases, offsets may only be sent for a subset of the levels. Higher levels may apply no offset, may apply an average offset, or may apply the offset used for the highest level having a level-specific offset.
Abstract:
Methods and devices for encoding and decoding data using transform domain filtering are described. The encoder determines a set of transform domain filter coefficients to be applied to a transform domain prediction. The filtering may, in some cases, also apply to transform domain reconstructions. Rate-distortion optimization may be used to determine the optimal filter coefficients on a frame-basis, coding-unit-basis, or other basis. Multiple filters may be developed and communicated from the encoder to the decoder for different combinations of transform block size, coding mode, prediction mode, and texture type. In other cases, the filtering is applied in the pixel-domain to a pixel-domain prediction or a pixel-domain reconstruction of a block of samples.
Abstract:
Methods and devices for video coding are described. When encoding a non-zero coefficient group (CG) prior to the last such group in a group scan ordering within a transform block, data representative of the true (x,y)-position of the last non-zero transform coefficient in a scan ordering within that CG is modified, to improve coding efficiency, based upon at least one of (a) an intra-prediction mode used to encode the block and (b) at least one coefficient group neighboring that CG. Upon decoding a CG thus encoded, the modification is un-done to retrieve the true (x,y)-position.
Abstract:
Methods, systems, and computer programs for encoding and decoding image are described. In some aspects, an input data block and a prediction data block are accessed. A projection factor is generated based on a projection of the input data block onto the prediction data block. A scaled prediction data block is generated by multiplying the projection factor by the prediction data block. A residual data block is generated based on a difference between the input data block and the scaled prediction data block. In some aspects, a prediction data block, a residual data block, and a projection factor associated with the residual data block are accessed. A scaled prediction data block is generated by multiplying the projection factor by the prediction data block. An output data block is generated by summing the residual data block and the scaled prediction data block.
Abstract:
Methods and devices are described for entropy coding data using an entropy coder to encode quantized transform domain coefficient data. Last significant coefficient information is signaled in the bitstream using two-dimensional coordinates for the last significant coefficient. The context for bins of one of the coordinates is based, in part, upon the value of the other of the coordinates. In one case, instead of signaling last significant coefficient information, the number of non-zero coefficients is binarized and entropy encoded.
Abstract:
Methods and devices for video coding are described. If an intra-prediction mode to be used in encoding a block of residual data is in a specific predetermined class, e.g., the horizontal class, then at least a portion of a quantized transformed block of residual data is transposed during encoding. Likewise, if an intra-prediction mode that was used to generate an encoded block of residual data is in such a class, then at least a portion of an entropy-decoded block of residual data is transposed during decoding.
Abstract:
Methods and devices for encoding and decoding video using mode-dependent context determination in the case of level-run pair coding of transform coefficients are described. Intra-coding modes may be grouped into classes and each class may be associated with a partitioning of a coefficient group into regions. The region in which a coefficient falls determines, in part, the context selected for encoding bins associated with that coefficient, including a level, if the coefficient is non-zero, and a run if the coefficient correspond to the bin of a binarized run value.
Abstract:
Methods and devices for reconstructing coefficient levels from a bitstream of encoded video data for a coefficient group in a transform unit. Sign bits are hidden in the parity of partially overlapping subsets of a set of coefficients. This enables the hiding of multiple sign bits per coefficient group. Other information bits may be hidden instead of sign bits in some cases.
Abstract:
An encoding method for encoding video data by adjusting a quantization parameter, the video data being partitioned into blocks comprising sets of quantized transform coefficients. The method includes, for a set of quantized transform coefficients corresponding to one of the blocks, collecting statistics, wherein the statistics comprise the number of quantized transform coefficients and the sum of the non-rounded quantization value of the quantized transform coefficients in the set. The method also includes deriving a step size based on the statistics, mapping the derived step size to a closest quantization parameter value, and quantizing a next block using the mapped quantization parameter value.