Light detection and ranging (LiDAR)data compression and decompression methods and apparatus
AssigneeUniversity of Maribor
InventorsBorut Zalik, Domen Mongus
Life of this patent
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Abstract
Methods and apparatus for lossless LiDAR LAS file compression and decompression are provided that include predictive coding, variable-length coding, and arithmetic coding. The predictive coding uses four different predictors including three predictors for x, y, and z coordinates and a constant predictor for scalar values, associated with each LiDAR data point.
Claims54
A method for compressing three dimensional LiDAR point data, the method comprising:
- receiving a dataset to be compressed, the dataset including a plurality of data points in a sequence,
- the data points each including at least four types of attribute values,
- the attribute value types including an X-coordinate value type, a Y-coordinate value type, a Z-coordinate value type, and at least one associated scalar value type;
- applying predictive coding to a sequence of attribute values of a same type from the dataset to generate a sequence of prediction errors for each of the X-coordinate value type and the scalar value type;
- applying predictive coding to a sequence of attribute values of a different type from the dataset to generate a sequence of prediction errors for each of the Y-coordinate value type and the Z-coordinate value type;
- applying variable length coding to the sequences of prediction errors to generate byte-streams of variable length codes;
- and
- compressing the byte-streams of variable length codes using entropy coding.
A medium comprising a non-transitory computer-readable medium including computer-executable instructions adapted to cause a computer to:
- receive a dataset to be compressed, the dataset including a plurality of LiDAR data points in a sequence, the data points each including at least four types of attribute values,
- the attribute value types including an X-coordinate value type, a Y-coordinate value type, a Z-coordinate value type, and at least one associated scalar value type;
- apply predictive coding to a sequence of attribute values of a same type from the dataset to generate a sequence of prediction errors for each of the X-coordinate value type and the scalar value type;
- apply predictive coding to a sequence of attribute values of a different type from the dataset to generate a sequence of prediction errors for each of the Y-coordinate value type and the Z-coordinate value type;
- apply variable length coding to the sequences of prediction errors to generate byte-streams of variable length codes;
- and
- compress the byte-streams of variable length codes using entropy coding.
A computer programmed to compress three dimensional LiDAR point data, the computer comprising:
- a processor;
- and
- a memory coupled to the processor and operable to store computer-executable instructions adapted to cause the computer to:
- receive a dataset to be compressed, the dataset including a plurality of data points in a sequence,
- the data points each including at least four types of attribute values, the attribute value types including an X-coordinate value type, a Y-coordinate value type, a Z-coordinate value type, and at least one associated scalar value type;
- apply predictive coding to a sequence of attribute values of a same type from the dataset to generate a sequence of prediction errors for a each of the X-coordinate value type and the scalar value type;
- apply predictive coding to a sequence of attribute values of a different type from the dataset to generate a sequence of prediction errors for each of the Y-coordinate value type and the Z-coordinate value type;
- apply variable length coding to the sequences of prediction errors to generate byte-streams of variable length codes;
- and
- compress the byte-streams of variable length codes using entropy coding.
Dependencies are inferred from the claim text.