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PubMed1997

Optimisation algorithms for ECG data compression.

The use of exact optimisation algorithms for compressing digital electrocardiograms (ECGs) is demonstrated. As opposed to traditional time-domain methods, which use heuristics to select a small subset of representative signal samples, the problem of selecting the subset is formulated in rigorous mathematical terms. This approach makes it possible to derive algorithms guaranteeing the smallest possible reconstruction error when a bounded selection of signal samples is interpolated. The proposed model resembles well-known network models and is solved by a cubic dynamic programming algorithm. When applied to standard test problems, the algorithm produces a compressed representation for which the distortion is about one-half of that obtained by traditional time-domain compression techniques at reasonable compression ratios. This illustrates that, in terms of the accuracy of decoded signals, existing time-domain heuristics for ECG compression may be far from what is theoretically achievable. The paper is an attempt to bridge this gap.

Algorithms↗
PubMed1991

Image data compression using a new floating-point digital signal processor.

A new dual-ported, floating-point, digital signal processor has been evaluated for compressing 512 and 1,024 digital radiographic images using a full-frame, two-dimensional, discrete cosine transform (2D-DCT). The floating point digital signal processor operates at 49.5 million floating point instructions per second (MFLOPS). The level of compression can be changed by varying four parameters in the lossy compression algorithm. Throughput times were measured for both 2D-DCT compression and decompression. For a 1,024 x 1,024 x 10-bit image with a compression ratio of 316:1, the throughput was 75.73 seconds (compression plus decompression throughput). For a digital fluorography 1,024 x 1,024 x 8-bit image and a compression ratio of 26:1, the total throughput time was 63.23 seconds. For a computed tomography image of 512 x 512 x 12 bits and a compression ratio of 10:1 the throughput time was 19.65 seconds.

Algorithms↗
PubMed1994

Joint photographic experts group (JPEG) compatible data compression of mammograms.

We have developed a Joint Photographic Experts Group (JPEG) compatible image compression scheme tailored to the compression of digitized mammographic images. This includes a preprocessing step that segments the tissue area from the background, replaces the background pixels with a constant value, and applies a noise-removal filter to the tissue area. The process was tested by performing a just-noticeable difference (JND) study to determine the relationship between compression ratio and a reader's ability to discriminate between compressed and noncompressed versions of digitized mammograms. We found that at compression ratios of 15:1 and below, image-processing experts are unable to detect a difference, whereas at ratios of 60:1 and above they can identify the compressed image nearly 100% of the time. The performance of less specialized viewers was significantly lower because these viewers seemed to have difficulty in differentiating between artifact and real information at the lower and middle compression ratios. This preliminary study suggests that digitized mammograms are very amenable to compression by techniques compatible with the JPEG standard. However, this study was not designed to address the efficacy of image compression process for mammography, but is a necessary first step in optimizing the compression in anticipation of more elaborate reader performance (ROC) studies.

Algorithms↗
PubMedDate not supplied

New trends in image data compression.

This paper gives an overview of a number of advanced techniques for image compression, which are under investigation in the Signal Processing Laboratory at the Swiss Federal Institute of Technology of Lausanne. Various applications ranging from High definition television (HDTV) to multimedia will be discussed. In particular, systems based on subband decomposition, edge based representation, as well as symmetries will be presented.

Artifacts↗
PubMed2000

ECG data compression using optimal non-orthogonal wavelet transform.

This paper introduces an effective technique for the compression of electrocardiogram (ECG) signals. The technique is based on a new class of non-orthogonal discrete wavelet transform (DWT). The performance of ECG compression algorithm is measured by its ability to minimize distortion while retaining all clinically significant features of the signal. The percent root-mean square difference (PRD) is used as an accepted standard for measuring the signal distortion. However, there is no standard for measuring the clinically significant features retained after signal reconstruction. The coefficients of the DWT are calculated such that the square of the difference between the original signal and the reconstructed one is minimum in least mean square sense. The resulting transforms deal with signals of arbitrary lengths; that means the signal length is not restricted to be a multiple of power of 2. Numerical results comparing the performance of the constructed non-orthogonal transform with that of W-transform and Daubechies D(4) orthogonal transform are given. These results show that, independent of signal length, the decomposition of the signal up to the fourth level is sufficient for getting minimum PRD. In addition, the proposed technique yields the lowest PRD compared to the other two algorithms and for a compression ratio less than 10 the optimal transform can be obtained for only one ECG period. However, for a higher compression ratio the PRD is smaller for long signals.

Algorithms↗
PubMedDate not supplied

Algorithmically compressed data and the topological conjecture for the inner-core electrons.

Eight different properties of three classes of compounds, metal halides, halomethanes, and chlorofluorocarbons, have been modeled with the aim to check the validity of the odd complete graph conjecture suggested for encoding the contribution of the inner-core electrons to the molecular connectivity indices. Modeling using this conjecture is compared with modeling using connectivity indices derived by other well-known algorithms. The conjecture of odd complete graph for the inner-core electrons achieves to improve the modeling quality of the molecular connectivity indices and/or of the molecular connectivity terms. The importance of the recently introduced dual molecular connectivity indices and pseudoindices in further refining the modeling quality of the higher-order terms has also been stressed.

Journal Article↗
PubMed1993

ECG data compression with time-warped polynomials.

This paper presents a new adaptive compression method for ECG's. The method represents each R-R interval by an optimally time-warped polynomial. It achieves a high-quality approximation at less than 250 bits/s. The article shows that the corresponding rates for other transform based schemes (the DCT and the DLT) are always higher. Also, the new method is less sensitive to errors in QRS detection and it removes more (white) noise from the signal. The reconstruction errors are distributed more uniformly in the new scheme and the peak error is usually lower. The reconstruction method is also useful for adaptive filtering of noisy ECG signals.

Algorithms↗
PubMed2000

A comparative study of transforms for use in digital audio data compression.

This paper provides a subjective quality analysis of transforms used in audio compression algorithms for a class of music signals. A 34-subject listener test compares three transforms in conjunction with an MPEG I layer 1 compression scheme. One test compares the performances of the discrete wavelet packet transform (DWPT) and the modified discrete cosine transform (MDCT) used in MPEG. Another test compares the performances of a DWPT eight-level nonuniform critical-band split and a DWPT five-level uniform subband split. Results indicate that the critical-band split provides significantly better quality than the uniform subband split for sounds with tonal and strong low-frequency content, while the DWPT outperforms the MDCT with significant improvement for nontonal sounds.

Algorithms↗