Mixed-transform based codec for 2D compression of ECG signals

Johan   Chagnon; Laura Rebollo-Neira

doi:10.1016/j.bspc.2020.102067

Mixed-transform based codec for 2D compression of ECG signals

Research output: Contribution to journal › Article › peer-review

Abstract

A method for ECG compression, by imaging the record as a 2D array and implementing a transform lossy compression strategy, is advanced. The particularity of the proposed transformation consists in applying a Discrete Wavelet Transform along one of the dimensions and the Discrete Cosine Transform along the other dimension. This renders a transformed array which is characterized by being sparse. Using the MIT-BIH Arrhythmia database, it is demonstrated that the proposed Mixed Transform achieves, in mean value, an improvement in sparsity of up to 3 times with respect to the 2D Wavelet Transform. This feature is beneficial for compression. The resulting codec produces a mean value compression ratio of 39 for a quality corresponding to PRD= 0.6. This PRD is attained for every record in the database without previous filtering.

Original language	English
Article number	102067
Journal	Biomedical Signal Processing and Control
Volume	62
Early online date	17 Jul 2020
DOIs	https://doi.org/10.1016/j.bspc.2020.102067
Publication status	Published - 1 Sept 2020

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10.1016/j.bspc.2020.102067

1908.03433
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https://arxiv.org/abs/1908.03433

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title = "Mixed-transform based codec for 2D compression of ECG signals",

abstract = "A method for ECG compression, by imaging the record as a 2D array and implementing a transform lossy compression strategy, is advanced. The particularity of the proposed transformation consists in applying a Discrete Wavelet Transform along one of the dimensions and the Discrete Cosine Transform along the other dimension. This renders a transformed array which is characterized by being sparse. Using the MIT-BIH Arrhythmia database, it is demonstrated that the proposed Mixed Transform achieves, in mean value, an improvement in sparsity of up to 3 times with respect to the 2D Wavelet Transform. This feature is beneficial for compression. The resulting codec produces a mean value compression ratio of 39 for a quality corresponding to PRD= 0.6. This PRD is attained for every record in the database without previous filtering.",

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N2 - A method for ECG compression, by imaging the record as a 2D array and implementing a transform lossy compression strategy, is advanced. The particularity of the proposed transformation consists in applying a Discrete Wavelet Transform along one of the dimensions and the Discrete Cosine Transform along the other dimension. This renders a transformed array which is characterized by being sparse. Using the MIT-BIH Arrhythmia database, it is demonstrated that the proposed Mixed Transform achieves, in mean value, an improvement in sparsity of up to 3 times with respect to the 2D Wavelet Transform. This feature is beneficial for compression. The resulting codec produces a mean value compression ratio of 39 for a quality corresponding to PRD= 0.6. This PRD is attained for every record in the database without previous filtering.

AB - A method for ECG compression, by imaging the record as a 2D array and implementing a transform lossy compression strategy, is advanced. The particularity of the proposed transformation consists in applying a Discrete Wavelet Transform along one of the dimensions and the Discrete Cosine Transform along the other dimension. This renders a transformed array which is characterized by being sparse. Using the MIT-BIH Arrhythmia database, it is demonstrated that the proposed Mixed Transform achieves, in mean value, an improvement in sparsity of up to 3 times with respect to the 2D Wavelet Transform. This feature is beneficial for compression. The resulting codec produces a mean value compression ratio of 39 for a quality corresponding to PRD= 0.6. This PRD is attained for every record in the database without previous filtering.

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Mixed-transform based codec for 2D compression of ECG signals

Abstract

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