CONTEXT MODELING TECHNIQUES FOR TRANSFORM COEFFICIENT LEVEL CODING
In one embodiment, a method for encoding video data is provided that includes receiving a transform unit comprising a two-dimensional array of transform coefficients and processing the transform coefficients of the two-dimensional array along a single-level scan order. The processing includes selecting, for each non-zero transform coefficient along the single-level scan order, one or more context models for encoding an absolute level of the non-zero transform coefficient, where the selecting is based on one or more transform coefficients previously encoded along the single-level scan order.
1 . A method for encoding video data comprising:
receiving, by a computing device, a transform unit comprising a two-dimensional array of transform coefficients; and
processing, by the computing device, the transform coefficients of the two-dimensional array along a single-level scan order,
wherein the processing comprises, for each non-zero transform coefficient along the single-level scan order, selecting one or more context models for encoding an absolute level of the non-zero transform coefficient, the selecting being based on one or more transform coefficients previously encoded along the single-level scan order.
2 . The method of claim 1 wherein selecting the one or more context models comprises selecting a first context model for a first syntax element associated with the non-zero transform coefficient, the first syntax element indicating whether the absolute level for the non-zero transform coefficient is greater than one.
3 . The method of claim 2 wherein selecting the first context model is based on a first threshold number of transform coefficients previously encoded along the single-level scan order that have an absolute level equal to one.
4 . The method of claim 3 wherein the first threshold number is equal to ten.
5 . The method of claim 2 wherein selecting the one or more context models further comprises selecting a second context model for a second syntax element associated with the non-zero transform coefficient, the second syntax element indicating whether the absolute level for the non-zero transform coefficient is greater than two.
6 . The method of claim 5 wherein selecting the second context model is based on a second threshold number of transform coefficients previously encoded along the single-level scan order that have an absolute level greater than one.
7 . The method of claim 6 wherein the second threshold number is equal to ten.
8 . The method of claim 1 wherein selecting the one or more context models is further based on a size of the transform unit.
9 . The method of claim 1 wherein the single-level scan order corresponds to a reverse zigzag scan or a reverse wavefront scan.
10 . A method for decoding video data comprising:
receiving, by a computing device, a bitstream of compressed data, the compressed data corresponding to a two-dimensional array of transform coefficients that were previously encoded along a single-level scan order; and
decoding, by the computing device, the bitstream of compressed data,
wherein the decoding comprises, for each non-zero transform coefficient along the single-level scan order, selecting one or more context models for decoding an absolute level of the non-zero transform coefficient, the selecting being based one or more transform coefficients previously decoded along the single-level scan order.
11 . The method of claim 10 wherein selecting the one or more context models comprises selecting a first context model for a first syntax element associated with the non-zero transform coefficient, the first syntax element indicating whether the absolute level for the transform coefficient is greater than one.
12 . The method of claim 11 wherein selecting the first context model is based on a first threshold number of transform coefficients previously decoded along the single-level scan order that have an absolute level equal to one.
13 . The method of claim 11 wherein selecting the one or more context models further comprises selecting a second context model for a second syntax element associated with the non-zero transform coefficient, the second syntax element indicating whether the absolute level for the non-zero transform coefficient is greater than two.
14 . A method of claim 13 wherein selecting the second context model is based on a second threshold number of transform coefficients previously decoded along the single-level scan order that have an absolute level greater than one.
15 . A method for encoding video data comprising:
receiving, by a computing device, a transform unit comprising a plurality of transform coefficients; and
encoding, by the computing device, a significance map of the transform unit and absolute levels of the plurality of transform coefficients using a single scan type and a single context model selection scheme.
16 . The method of claim 15 wherein the single scan type is a forward zigzag scan, a reverse zigzag scan, a forward wavefront scan, or a reverse wavefront scan.
17 . The method of claim 16 wherein the single context model selection scheme is a neighbor-based scheme that selects, for each transform coefficient in the plurality of transform coefficients, a context model for the transform coefficient based on one or more neighbor transform coefficients previously encoded along the single scan type.
18 . A method for decoding video data comprising:
receiving, by a computing device, a bitstream of compressed data, the compressed data corresponding to a transform unit comprising a plurality of transform coefficients that were previously encoded; and
decoding, by the computing device, a significance map of the transform unit and absolute levels of the plurality of transform coefficients using a single scan type and a single context model selection scheme.
19 . The method of claim 18 wherein the single scan type is a forward zigzag scan, a reverse zigzag scan, a forward wavefront scan, or a reverse wavefront scan.
20 . The method of claim 18 wherein the single context model selection scheme is a neighbor-based scheme that selects, for each transform coefficient in the plurality of transform coefficients, a context model for the transform coefficient based on one or more neighbor transform coefficients previously decoded along the single scan type.