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Compression of 3D point clouds using 1D discrete cosine transform
- Source :
- ISPACS
- Publication Year :
- 2017
- Publisher :
- IEEE, 2017.
-
Abstract
- Discrete cosine transform is an ideal method to decorrelate the signal. In this paper, we proposed a novel entropy coding based on 1D-DCT to compress the 3D point clouds. Different from the former method which is based on Laplacian distribution, we encoding the coefficients by count the nonzero coefficients. We count the number, index, value of the nonzero coefficients of each block and then use arithmetic encoder to compress the coefficient. Experimental results on a number of point clouds show our method is more efficient than the former method based on DCT.
- Subjects :
- ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
MathematicsofComputing_NUMERICALANALYSIS
0211 other engineering and technologies
Point cloud
Data_CODINGANDINFORMATIONTHEORY
02 engineering and technology
Signal
Laplace distribution
Compression (functional analysis)
Encoding (memory)
ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION
021105 building & construction
0202 electrical engineering, electronic engineering, information engineering
Discrete cosine transform
020201 artificial intelligence & image processing
Entropy encoding
Algorithm
Mathematics
Block (data storage)
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)
- Accession number :
- edsair.doi...........dc8b81e617426bd9726cc43c10ad5410
- Full Text :
- https://doi.org/10.1109/ispacs.2017.8266472