Entropy coding supporting mode switching

1. A decoder for decoding a data stream including encoded data of a video, the decoder comprising:

an entropy decoding engine configured to entropy decode data from the data stream using a selected one of a plurality of entropy decoding schemes to obtain a sequence of symbols, wherein each of the plurality of entropy decoding schemes involves arithmetic decoding of symbols, and the selection of the one of the plurality of entropy decoding schemes is in accordance with a low complexity mode or a high-efficiency mode,

wherein, for at least one symbol of the sequence of symbols, the entropy decoding engine is configured to:

select a context corresponding to the at least one symbol, the selected context corresponding to a probability model, and

entropy decode the at least one symbol using the selected one of a plurality of entropy decoding schemes based on the selected context, wherein the probability model is updated at a first update rate under the high-efficiency mode and a second update rate lower than the first update rate under the low-complexity mode;

a desymbolizer configured to desymbolize the sequence of symbols to obtain a sequence of syntax elements; and

a reconstructor configured to reconstruct at least a portion of the video based on the sequence of syntax elements.

2. The decoder of claim 1 , wherein the selection depends on previously retrieved symbols of the sequence of symbols in case of the high-efficiency mode being activated and independent from any previously retrieved symbols of the sequence of symbols in case of the low-complexity mode being activated.

3. The decoder of claim 1 , wherein the data stream is structured into consecutive portions and each symbol of the sequence of symbols is associated with a respective one of a plurality of symbol types, wherein, for symbols of a predetermined symbol type within a current portion, the selection varies depending on previously retrieved symbols of the sequence of symbols of the predetermined symbol type within the current portion in case of the high-efficiency mode being activated, and is constant within the current portion in case of the low-complexity mode being activated.

4. The decoder of claim 1 , wherein each symbol of the sequence of symbols is associated with a respective one of a plurality of symbol types, wherein for each symbol of a predetermined symbol type, the selection of the one of the plurality of entropy decoding schemes depends on a probability model associated with the predetermined symbol type.

5. The decoder of claim 1 , wherein the probability model is associated with a probability state index having a first probability state accuracy for the high-efficiency mode, and a second probability state accuracy, lower than the first probability state accuracy, for the low-complexity mode.

6. The decoder of claim 1 , wherein the data stream comprises information associated with color samples of the video.

7. The decoder of claim 1 , wherein the data stream comprises information associated with a depth map of the video.

8. An encoder for encoding data of a video into a data stream, the encoder comprising:

a constructor configured to encode the data of the video into a sequence of syntax elements;

a symbolizer configured to symbolize the sequence of syntax elements into a sequence of symbols; and

an entropy encoding engine configured to encode each symbol of the sequence of symbols into the data stream using a selected one of a plurality of entropy encoding schemes, wherein each of the plurality of entropy decoding schemes involves arithmetic decoding of symbols, and the entropy encoding engine is configured to perform the selection of the one of the plurality of entropy encoding schemes in accordance with a low complexity mode or a high-efficiency mode, and

wherein, for at least one symbol of the sequence of symbols, the entropy encoding engine is configured to:

select a context corresponding to the at least one symbol, the selected context corresponding to a probability model, and

entropy encode the at least one symbol using the selected one of a plurality of entropy encoding schemes based on the selected context, wherein the probability model is updated at a first update rate under the high-efficiency mode, and is updated at a second update rate lower than the first update rate under the low-complexity mode.

9. The encoder of claim 8 , wherein the selection depends on previously retrieved symbols of the sequence of symbols in case of the high-efficiency mode being activated and independent from any previously retrieved symbols of the sequence of symbols in case of the low-complexity mode being activated.

10. The encoder of claim 8 , wherein the data stream is structured into consecutive portions and each symbol of the sequence of symbols is associated with a respective one of a plurality of symbol types, wherein, for symbols of a predetermined symbol type within a current portion, the selection varies depending on previously retrieved symbols of the sequence of symbols of the predetermined symbol type within the current portion in case of the high-efficiency mode being activated, and is left constant within the current portion in case of the low-complexity mode being activated.

11. The encoder of claim 8 , wherein each symbol of the sequence of symbols is associated with a respective one of a plurality of symbol types, wherein for each symbol of a predetermined symbol type, the selection of the one of the plurality of entropy decoding schemes depends on a probability model associated with the predetermined symbol type.

12. The encoder of claim 8 , wherein the probability model is associated with a probability state index having a first probability state accuracy for the high-efficiency mode, and a second probability state accuracy, lower than the first probability state accuracy, for the low-complexity mode.

13. The encoder of claim 8 , wherein the data stream comprises information associated with color samples of the video.

14. The encoder of claim 8 , wherein the data stream comprises information associated with a depth map of the video.

15. A method for decoding a data stream including encoded data of a video, the method comprising:

entropy decoding data from the data stream using a selected one of a plurality of entropy decoding schemes to obtain a sequence of symbols, wherein each of the plurality of entropy decoding schemes involves arithmetic decoding of symbols, and the selection of the one of the plurality of entropy decoding schemes is in accordance with a low complexity mode or a high-efficiency mode, wherein, for at least one symbol of the sequence of symbols, the entropy decoding comprises:

selecting a context corresponding to the at least one symbol, the selected context corresponding to a probability model, and

entropy decoding the at least one symbol using the selected one of a plurality of entropy decoding schemes based on the selected context, wherein the probability model is updated at a first update rate under the high-efficiency mode, and is updated at a second update rate lower than the first update rate under the low-complexity mode;

desymbolizing the sequence of symbols in order to acquire a sequence of syntax elements; and

reconstructing at least a portion of the video based on the sequence of syntax elements.

16. The method of claim 15 , wherein the selection depends on previously retrieved symbols of the sequence of symbols in case of the high-efficiency mode being activated and independent from any previously retrieved symbols of the sequence of symbols in case of the low-complexity mode being activated.

17. The method of claim 15 , wherein the data stream is structured into consecutive portions and each symbol of the sequence of symbols is associated with a respective one of a plurality of symbol types, wherein, for symbols of a predetermined symbol type within a current portion, the selection varies depending on previously retrieved symbols of the sequence of symbols of the predetermined symbol type within the current portion in case of the high-efficiency mode being activated, and is constant within the current portion in case of the low-complexity mode being activated.

18. The method of claim 15 , wherein each symbol of the sequence of symbols is associated with a respective one of a plurality of symbol types, wherein for each symbol of a predetermined symbol type, the selection of the one of the plurality of entropy decoding schemes depends on a probability model associated with the predetermined symbol type.

19. The method of claim 15 , wherein the probability model is associated with a probability state index having a first probability state accuracy for the high-efficiency mode, and a second probability state accuracy, lower than the first probability state accuracy, for the low-complexity mode.

20. The method of claim 15 , wherein the data stream comprises information associated with color samples of the video.

21. The method of claim 15 , wherein the data stream comprises information associated with a depth map of the video.

22. A non-transitory computer-readable medium for storing data associated with a video, comprising:

a data stream stored in the non-transitory computer-readable medium, the data stream comprising an encoded sequence of symbols of a video, wherein the sequence of symbols is encoded into the data stream based on a plurality of operations comprising:

encoding the data of the video into a sequence of syntax elements;

symbolizing the sequence of syntax elements into a sequence of symbols; and

entropy encoding each symbol of the sequence of symbols into the data stream using a selected one of a plurality of entropy encoding schemes,

wherein each of the plurality of entropy decoding schemes involves arithmetic decoding of symbols, and the selection of the one of the plurality of entropy encoding schemes is performed in accordance with a low complexity mode or a high-efficiency mode, and

wherein, for at least one symbol of the sequence of symbols, the entropy encoding comprises:

selecting a context corresponding to the at least one symbol, the selected context corresponding to a probability model, and

entropy encoding the at least one symbol using the selected one of a plurality of entropy encoding schemes based on the selected context, wherein the probability model is updated at a first update rate under the high-efficiency mode, and is updated at a second update rate lower than the first update rate under the low-complexity mode.

23. The non-transitory computer-readable medium of claim 22 , wherein the data stream comprises information associated with color samples of the video.

24. The non-transitory computer-readable medium of claim 22 , wherein the data stream comprises information associated with a depth map of the video.

25. The non-transitory computer-readable medium of claim 22 , wherein the selection depends on previously retrieved symbols of the sequence of symbols in case of the high-efficiency mode being activated and independent from any previously retrieved symbols of the sequence of symbols in case of the low-complexity mode being activated.

26. The non-transitory computer-readable medium of claim 22 , wherein the data stream is structured into consecutive portions and each symbol of the sequence of symbols is associated with a respective one of a plurality of symbol types, wherein, for symbols of a predetermined symbol type within a current portion, the selection varies depending on previously retrieved symbols of the sequence of symbols of the predetermined symbol type within the current portion in case of the high-efficiency mode being activated, and is constant within the current portion in case of the low-complexity mode being activated.

27. The non-transitory computer-readable medium of claim 22 , wherein each symbol of the sequence of symbols is associated with a respective one of a plurality of symbol types, wherein for each symbol of a predetermined symbol type, the selection of the one of the plurality of entropy decoding schemes depends on a probability model associated with the predetermined symbol type.

28. The non-transitory computer-readable medium of claim 22 , wherein the probability model is associated with a probability state index having a first probability state accuracy for the high-efficiency mode, and a second probability state accuracy, lower than the first probability state accuracy, for the low-complexity mode.

29. A non-transitory computer-readable medium comprising a computer program for performing, when running on a computer, a method of claim 15 .

30. The non-transitory computer-readable medium of claim 29 , wherein the data stream comprises information associated with color samples of the video.