Three-dimensional data encoding method, three-dimensional data decoding method, three-dimensional data encoding device, and three-dimensional data decoding device

1. A three-dimensional data encoding method, comprising:

transforming pieces of attribute information of three-dimensional points included in point cloud data into coefficient values; and

encoding the coefficient values to generate a bitstream,

wherein in the transforming, a weighting calculation is performed hierarchically to generate the coefficient values, each of the coefficient values belonging to a corresponding one of layers, the weighting calculation separating each of the pieces of attribute information into a high-frequency component and a low-frequency component,

in the weighting calculation, the weighting calculation is performed using weights fixed or not fixed in the layers,

the bitstream includes first information indicating whether to fix the weights in the layers, and

in the weighting calculation, when the first information indicates that the weights are fixed in the layers, all weights used in the layers are fixed.

2. The three-dimensional data encoding method according to claim 1 ,

wherein when the weights are fixed in the layers, the weights are fixed to 1.

3. The three-dimensional data encoding method according to claim 1 ,

wherein in the weighting calculation:

first attribute information is subtracted from second attribute information to calculate a first value, the first attribute information and the second attribute information being included in the pieces of attribute information; and

the first value is divided by a first coefficient to calculate the high-frequency component, and

the first coefficient depends on a quantization step and the weights.

4. The three-dimensional data encoding method according to claim 3 ,

wherein in the weighting calculation:

the first value is multiplied by a second coefficient depending on the weights to calculate a second value;

the second value is shifted down by a predetermined bit count and shifted up by the predetermined bit count to calculate a third value; and

the third value is added to the first attribute information to calculate the low-frequency component.

5. A three-dimensional data decoding method, comprising:

obtaining, from a bitstream, first information indicating whether to fix weights in layers;

decoding coefficient values from the bitstream; and

inverse transforming the coefficient values to generate pieces of attribute information of three-dimensional points included in point cloud data,

wherein the coefficient values belong to one of the layers,

in the inverse transforming, an inverse weighting calculation is performed to generate the pieces of attribute information, the inverse weighting calculation combining the coefficient values with a high-frequency component and a low-frequency component,

in the inverse weighting calculation, the inverse weighting calculation is performed using the weights fixed or not fixed in the layers, according to the first information, and

in the inverse weighting calculation, when the first information indicates that the weights are fixed in the layers, all weights used in the layers are fixed.

6. The three-dimensional data decoding method according to claim 5 ,

wherein when the weights are fixed in the layers, the weights are fixed to 1.

7. The three-dimensional data decoding method according to claim 5 ,

wherein in the inverse weighting calculation:

the high-frequency component is multiplied by a first coefficient to calculate a first value;

first attribute information included in the pieces of attribute information is calculated from a second value based on the low-frequency component; and

the second value is subtracted from the first value to calculate second attribute information included in the pieces of attribute information, and

the first coefficient depends on a quantization step and the weights.

8. The three-dimensional data decoding method according to claim 7 ,

wherein in the inverse weighting calculation:

the first value is multiplied by a second coefficient depending on the weights to calculate a third value;

the third value is shifted down by a predetermined bit count and shifted up by the predetermined bit count to calculate a fourth value; and

the low-frequency component is subtracted from the fourth value to calculate the second value.

9. A three-dimensional data encoding device, comprising:

a processor; and

a memory,

wherein using the memory, the processor:

transforms pieces of attribute information of three-dimensional points included in point cloud data into coefficient values; and

encodes the coefficient values to generate a bitstream,

wherein in the transforming, a weighting calculation is performed hierarchically to generate the coefficient values, each of the coefficient values belonging to a corresponding one of layers, the weighting calculation separating each of the pieces of attribute information into a high-frequency component and a low-frequency component,

in the weighting calculation, the weighting calculation is performed using weights fixed or not fixed in the layers,

the bitstream includes first information indicating whether to fix the weights in the layers, and

in the weighting calculation, when the first information indicates that the weights are fixed in the layers, all weights used in the layers are fixed.

10. A three-dimensional data decoding device, comprising:

a processor; and

a memory,

wherein using the memory, the processor:

obtains, from a bitstream, first information indicating whether to fix weights in layers;

decodes coefficient values from the bitstream; and

inverse transforms the coefficient values to generate pieces of attribute information of three-dimensional points included in point cloud data,

wherein the coefficient values belong to one of the layers,

in the inverse transforming, an inverse weighting calculation is performed to generate the pieces of attribute information, the inverse weighting calculation combining the coefficient values with a high-frequency component and a low-frequency component,

in the inverse weighting calculation, the inverse weighting calculation is performed using the weights fixed or not fixed in the layers, according to the first information, and

in the inverse weighting calculation, when the first information indicates that the weights are fixed in the layers, all weights used in the layers are fixed.