A refinement of the Embedded Zerotree Wavelet algorithm. SPIHT requires partitioning the wavelet coefficients into a number of lists, with list membership changing as the execution proceeds, and in some cases involving dual membership of a coefficient in different lists.
Published in Chapter:
Biomedical Signal Compression
Pedro de A. Berger (University of Brasilia, Brazil), Francisco A. de O. Nascimento (University of Brasilia, Brazil), Leonardo R.A.X. de Menezes (University of Brasilia, Brazil), Adson F. da Rocha (University of Brasilia, Brazil), and Joao L.A. Carvalho (University of Southern California, USA)
Copyright: © 2008
|Pages: 10
DOI: 10.4018/978-1-59904-889-5.ch022
Abstract
Digitization of biomedical signals has been used in several areas. Some of these include ambulatory monitoring, phone line transmission, database storage, and several other applications in health and biomedical engineering. These applications have helped in diagnostics, patient care, and remote treatment. One example is the digital transmission of ECG signals, from the patient’s house or ambulance to the hospital. This has been proven useful in cardiac diagnoses. Biomedical signals need to be digitally stored or transmitted with a large number of samples per second, and with a great number of bits per sample, in order to assure the required fidelity of the waveform for visual inspection. Therefore, the use of signal compression techniques is fundamental for cost reduction and technical feasibility of storage and transmission of biomedical signals.