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

被引：14
|
作者：
Puthooran, Emjee [1 ]
Anand, R. S. [1 ]
Mukherjee, S. [1 ]
机构：
[1] Indian Inst Technol Roorkee, Dept Elect Engn, Roorkee 247667, Uttarakhand, India
来源：
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS | 2013年 / 6卷 / 06期
关键词：
dual level DPCM (DL-DPCM); neural networks; lossless image compression; medical image; ALGORITHM;
D O I：
10.1080/18756891.2013.816059
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：1082 / 1093
页数：12
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