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Lossless Compression of Medical Images Using a Dual Level DPCM with Context Adaptive Switching Neural Network Predictor
- Source :
- International Journal of Computational Intelligence Systems, Vol 6, Iss 6 (1970), International Journal of Computational Intelligence Systems, Vol 6, Iss 6 (2013)
- Publication Year :
- 1970
- Publisher :
- Atlantis Press, 1970.
-
Abstract
- A novel dual level differential pulse code modulation (DL-DPCM) is proposed for lossless compression of medical images. The DL-DPCM consists of a linear DPCM followed by a nonlinear DPCM namely, context adaptive switching neural network predictor (CAS-NNP). The CAS-NNP adaptively switches between three NN predictors based on the context texture of the predicted pixel in the image. Experiments on magnetic resonance (MR) images showed lower prediction error for the DL-DPCM compared to the GAP and the MED, which are used in benchmark algorithms CALIC and LOCO-I respectively. The overall improvement in data reduction after entropy coding the prediction error were 0.21 bpp (6.5%) compared to the CALIC and 0.40 bpp (11.7%) compared to the LOCO-I.
- Subjects :
- Lossless compression
General Computer Science
Artificial neural network
Pixel
Computer science
business.industry
Speech recognition
lossless image compression
Pattern recognition
Context (language use)
computer.file_format
neural networks
lcsh:QA75.5-76.95
medical image
Computational Mathematics
Nonlinear system
Benchmark (computing)
Entropy encoding
Artificial intelligence
lcsh:Electronic computers. Computer science
business
Pulse-code modulation
computer
dual level DPCM (DL-DPCM)
Subjects
Details
- Language :
- English
- ISSN :
- 18756883
- Volume :
- 6
- Issue :
- 6
- Database :
- OpenAIRE
- Journal :
- International Journal of Computational Intelligence Systems
- Accession number :
- edsair.doi.dedup.....d558e23cd1742adf7fa6acaabcc92826