Lossless Compression of Medical Images Using a Dual Level DPCM with Context Adaptive Switching Neural Network Predictor

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 th...

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Main Authors: Emjee Puthooran, R S Anand, S Mukherjee
Format: Article
Language:English
Published: Springer 2013-12-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Online Access:https://www.atlantis-press.com/article/25868442.pdf
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author Emjee Puthooran
R S Anand
S Mukherjee
author_facet Emjee Puthooran
R S Anand
S Mukherjee
author_sort Emjee Puthooran
collection DOAJ
description 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.
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spelling doaj.art-0d08de7bd9414a31afceeeb27776075a2022-12-22T00:41:17ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832013-12-016610.1080/18756891.2013.816059Lossless Compression of Medical Images Using a Dual Level DPCM with Context Adaptive Switching Neural Network PredictorEmjee PuthooranR S AnandS MukherjeeA 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.https://www.atlantis-press.com/article/25868442.pdfdual level DPCM (DL-DPCM)neural networkslossless image compressionmedical image
spellingShingle Emjee Puthooran
R S Anand
S Mukherjee
Lossless Compression of Medical Images Using a Dual Level DPCM with Context Adaptive Switching Neural Network Predictor
International Journal of Computational Intelligence Systems
dual level DPCM (DL-DPCM)
neural networks
lossless image compression
medical image
title Lossless Compression of Medical Images Using a Dual Level DPCM with Context Adaptive Switching Neural Network Predictor
title_full Lossless Compression of Medical Images Using a Dual Level DPCM with Context Adaptive Switching Neural Network Predictor
title_fullStr Lossless Compression of Medical Images Using a Dual Level DPCM with Context Adaptive Switching Neural Network Predictor
title_full_unstemmed Lossless Compression of Medical Images Using a Dual Level DPCM with Context Adaptive Switching Neural Network Predictor
title_short Lossless Compression of Medical Images Using a Dual Level DPCM with Context Adaptive Switching Neural Network Predictor
title_sort lossless compression of medical images using a dual level dpcm with context adaptive switching neural network predictor
topic dual level DPCM (DL-DPCM)
neural networks
lossless image compression
medical image
url https://www.atlantis-press.com/article/25868442.pdf
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