Journal of Biomedical Science and Engineering

Volume 5, Issue 12 (December 2012)

ISSN Print: 1937-6871   ISSN Online: 1937-688X

Google-based Impact Factor: 1.12  Citations  h5-index & Ranking

Multimodal compression applied to biomedical data

HTML  Download Download as PDF (Size: 1438KB)  PP. 755-761  
DOI: 10.4236/jbise.2012.512094    3,231 Downloads   4,819 Views   Citations

ABSTRACT

In this paper, we introduce a novel approach to compress jointly a medical image and a multichannel bio-signals (e.g. ECG, EEG). This technique is based on the idea of Multimodal Compression (MC) which requires only one codec instead of multiple codecs. Objectively, biosignal samples are merged in the spatial domain of the image using a specific mixing function. Afterwards, the whole mixture is compressed using JPEG 2000. The spatial mixing function inserts samples in low-frequency regions, defined using a set of operations, including down-sampling, interpolation, and quad-tree decomposition. The decoding is achieved by inverting the process using a separation function. Results show that this technique allows better performances in terms of Compression Ratio (CR) compared to approaches which encode separately modalities. The reconstruction quality is evaluated on a set of test data using the PSNR (Peak Signal Noise Ratio) and the PRD (Percent Root Mean Square Difference), respectively for the image and biosignals.

Cite this paper

Zeybek, E. , Fournier, R. and Naït-Ali, A. (2012) Multimodal compression applied to biomedical data. Journal of Biomedical Science and Engineering, 5, 755-761. doi: 10.4236/jbise.2012.512094.

Cited by

[1] Biomedical Signal Analysis and Its Physio-Clinical Perspectives
2017
[2] A New Wavelet Based Bio-Medical Data Compression Scheme Using FPGA
International Journal of Innovative Research in Science, Engineering and Technology, 2017
[3] An improved multimodal signal-image compression scheme with application to natural images and biomedical data
Multimedia Tools and Applications, 2016

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.