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At least 199 records · Page 11Linked to original sources
PubMed2000

Assessment of visually lossless irreversible image compression: comparison of three methods by using an image-comparison workstation.

PURPOSE: To determine the degree of irreversible image compression detectable in conservative viewing conditions. MATERIALS AND METHODS: An image-comparison workstation, which alternately displayed two registered and magnified versions of an image, was used to study observer detection of image degradation introduced by irreversible compression. Five observers evaluated 20 16-bit posteroanterior digital chest radiographs compressed with Joint Photographic Experts Group (JPEG) or wavelet-based trellis-coded quantization (WTCQ) algorithms at compression ratios of 8:1-128:1 and x2 magnification by using (a) traditional two-alternative forced choice; (b) original-revealed two-alternative forced choice, in which the noncompressed image is identified to the observer; and (c) a resolution-metric method of matching test images to degraded reference images. RESULTS: The visually lossless threshold was between 8:1 and 16:1 for four observers. JPEG compression resulted in performance as good as that with WTCQ compression at these ratios. The original-revealed forced-choice method was faster and as sensitive as the two-alternative forced-choice method. The resolution-metric results were robust and provided information on performance above visually lossless levels. CONCLUSION: The image-comparison workstation is a versatile tool for comparative assessment of image quality. At x2 magnification, images compressed with either JPEG or WTCQ algorithms were indistinguishable from unaltered original images for most observers at compression ratios between 8:1 and 16:1, indicating that 10:1 compression is acceptable for primary image interpretation.

Algorithms↗
PubMed2004

Analysis and design of watermarking algorithms for improved resistance to compression.

We study the performance of robust digital watermarking approaches in the presence of lossy compression by introducing practical analysis methodologies. Correlation expressions between the embedded watermark and the extracted watermark are derived to determine the optimal watermarking domain to maximize data hiding rates for spread spectrum and quantization watermarking. It is determined both theoretically and through simulations that the embedding strategy, in addition to the transform used for lossy compression, dictate the optimal transform for watermarking. Through analytic comparisons, we develop a novel hybrid watermarking algorithm that exploits the best of both approaches for greater resilience to JPEG compression.

Algorithms↗
PubMed1999

The diagnostic validity of digitally captured intraoperative transesophageal echocardiography examinations compared with analog recordings: A pilot study.

BACKGROUND: Digital acquisition and storage of echocardiographic studies offer many advantages over analog recordings, but the amount of computer memory required may be large. "Computer compression" of data is done by machines with various algorithms. "Clinical compression" involves limiting the recordings to 1-beat loops, and although it is commonly used, its diagnostic validity has not been demonstrated in the operating room. METHODS: This prospective pilot study looked at 51 patients undergoing transesophageal echocardiography during cardiac surgery. During continuous videocassette recording, we captured digital loops to demonstrate wall motion abnormalities, ventricular systolic function, aortic insufficiency, and mitral regurgitation. Experts reviewed the loops and tapes. We then compared the diagnoses from the 2 methods. RESULTS: There were major differences in the diagnosis of wall motion between loops and tapes in only 3.4% of myocardial segments. No major differences were seen in the diagnosis of systolic function, aortic insufficiency, or mitral regurgitation in any patients. CONCLUSION: We conclude that clinical compression is a suitable method to compress data in the operating room. Large numbers of patients are required to definitively demonstrate the small differences.

Chi-Square Distribution↗
PubMed1999

[A wavelet neural network algorithm of EEG signals data compression and spikes recognition].

A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented. The wavelet network not only can compress data effectively but also can recover original signal. In addition, the characters of the spikes and the spike-slow rhythm are auto-detected from the time-frequency isoline of EEG signal. This method is well worth using in the field of the electrophysiological signal processing and time-frequency analyzing.

Adult↗
PubMed2000

[Wavelet packet-based ECG compression].

A wavelet packet-based algorithm for the compression of ECG is presented in the paper. The wavclet packet algorithm, which synthesizes the efficiency and the flexibility of the wavelet pacheket, generates significantly lower data rates with less computational effort.

Algorithms↗
PubMed2000

Wavelet compression of ECG signals by the set partitioning in hierarchical trees algorithm.

A wavelet electrocardiogram (ECG) data codec based on the set partitioning in hierarchical trees (SPIHT) compression algorithm is proposed in this paper. The SPIHT algorithm [1] has achieved notable success in still image coding. We modified the algorithm for the one-dimensional case and applied it to compression of ECG data. Experiments on selected records from the MIT-BIH arrhythmia database revealed that the proposed codec is significantly more efficient in compression and in computation than previously proposed ECG compression schemes. The coder also attains exact bit rate control and generates a bit stream progressive in quality or rate.

Algorithms↗
PubMedDate not supplied

Human motion capture data compression by model-based indexing: a power aware approach.

Human Motion Capture (MoCap) data can be used for animation of virtual human-like characters in distributed virtual reality applications and networked games. MoCap data compressed using the standard MPEG-4 encoding pipeline comprising of predictive encoding (and/or DCT decorrelation), quantization, and arithmetic/Huffman encoding, entails significant power consumption for the purpose of decompression. In this paper, we propose a novel algorithm for compression of MoCap data, which is based on smart indexing of the MoCap data by exploiting structural information derived from the skeletal virtual human model. The indexing algorithm can be fine-controlled using three predefined quality control parameters (QCPs). We demonstrate how an efficient combination of the three QCPs results in a lower network bandwidth requirement and reduced power consumption for data decompression at the client end when compared to standard MPEG-4 compression. Since the proposed algorithm exploits structural information derived from the skeletal virtual human model, it is observed to result in virtual human animation of visually acceptable quality upon decompression.

Algorithms↗
PubMed1994

MR image compression using a wavelet transform coding algorithm.

We present here a technique for MR image compression. It is based on a transform coding scheme using the wavelet transform and vector quantization. Experimental results show that the method offers high compression ratios with low degradation of the image quality. The technique is expected to be particularly useful wherever storing and transmitting large numbers of images is necessary.

Algorithms↗
PubMed2005

A joint compression-discrimination neural transformation applied to target detection.

Many image recognition algorithms based on data-learning perform dimensionality reduction before the actual learning and classification because the high dimensionality of raw imagery would require enormous training sets to achieve satisfactory performance. A potential problem with this approach is that most dimensionality reduction techniques, such as principal component analysis (PCA), seek to maximize the representation of data variation into a small number of PCA components, without considering interclass discriminability. This paper presents a neural-network-based transformation that simultaneously seeks to provide dimensionality reduction and a high degree of discriminability by combining together the learning mechanism of a neural-network-based PCA and a backpropagation learning algorithm. The joint discrimination-compression algorithm is applied to infrared imagery to detect military vehicles.

Algorithms↗
PubMed1997

Improving the efficiency of the genetic code by varying the codon length--the perfect genetic code.

The function of DNA is to specify protein sequences. The four-base "alphabet" used in nucleic acids is translated to the 20 base alphabet of proteins (plus a stop signal) via the genetic code. The code is neither overlapping nor punctuated, but has mRNA sequences read in successive triplet codons until reaching a stop codon. The true genetic code uses three bases for every amino acid. The efficiency of the genetic code can be significantly increased if the requirement for a fixed codon length is dropped so that the more common amino acids have shorter codon lengths and rare amino acids have longer codon lengths. More efficient codes can be derived using the Shannon-Fano and Huffman coding algorithms. The compression achieved using a Huffman code cannot be improved upon. I have used these algorithms to derive efficient codes for representing protein sequences using both two and four bases. The length of DNA required to specify the complete set of protein sequences could be significantly shorter if transcription used a variable codon length. The restriction to a fixed codon length of three bases means that it takes 42% more DNA than the minimum necessary, and the genetic code is 70% efficient. One can think of many reasons why this maximally efficient code has not evolved: there is very little redundancy so almost any mutation causes an amino acid change. Many mutations will be potentially lethal frame-shift mutations, if the mutation leads to a change in codon length. It would be more difficult for the machinery of transcription to cope with a variable codon length. Nevertheless, in the strict and narrow sense of coding for protein sequences using the minimum length of DNA possible, the Huffman code derived here is perfect.

Algorithms↗
PubMed2005

Optimal block boundary pre/postfiltering for wavelet-based image and video compression.

This paper presents a pre/postfiltering framework to reduce the reconstruction errors near block boundaries in wavelet-based image and video compression. Two algorithms are developed to obtain the optimal filter, based on boundary filter bank and polyphase structure, respectively. A low-complexity structure is employed to approximate the optimal solution. Performances of the proposed method in the removal of JPEG 2000 tiling artifact and the jittering artifact of three-dimensional wavelet video coding are reported. Comparisons with other methods demonstrate the advantages of our pre/postfiltering framework.

Algorithms↗
PubMedDate not supplied

Video on the Internet: An introduction to the digital encoding, compression, and transmission of moving image data.

In this paper, we seek to provide an introduction to the fast-moving field of digital video on the Internet, from the viewpoint of the biological microscopist who might wish to store or access videos, for instance in image databases such as the BioImage Database (http://www.bioimage.org). We describe and evaluate the principal methods used for encoding and compressing moving image data for digital storage and transmission over the Internet, which involve compromises between compression efficiency and retention of image fidelity, and describe the existing alternate software technologies for downloading or streaming compressed digitized videos using a Web browser. We report the results of experiments on video microscopy recordings and three-dimensional confocal animations of biological specimens to evaluate the compression efficiencies of the principal video compression-decompression algorithms (codecs) and to document the artefacts associated with each of them. Because MPEG-1 gives very high compression while yet retaining reasonable image quality, these studies lead us to recommend that video databases should store both a high-resolution original version of each video, ideally either uncompressed or losslessly compressed, and a separate edited and highly compressed MPEG-1 preview version that can be rapidly downloaded for interactive viewing by the database user.

Algorithms↗
PubMed2004

Morse description and geometric encoding of digital elevation maps.

Two complementary geometric structures for the topographic representation of an image are developed in this work. The first one computes a description of the Morse-topological structure of the image, while the second one computes a simplified version of its drainage structure. The topographic significance of the Morse and drainage structures of digital elevation maps (DEMs) suggests that they can been used as the basis of an efficient encoding scheme. As an application, we combine this geometric representation with an interpolation algorithm and lossless data compression schemes to develop a compression scheme for DEMs. This algorithm achieves high compression while controlling the maximum error in the decoded elevation map, a property that is necessary for the majority of applications dealing with DEMs. We present the underlying theory and compression results for standard DEM data.

Algorithms↗
PubMed2002

A quality-on-demand algorithm for wavelet-based compression of electrocardiogram signals.

For the compression of medical signals such as electrocardiogram (ECG), excellent reconstruction quality of a highly compressed signal can be obtained by using a wavelet-based approach. The most widely used objective quality criterion for the compressed ECG is called the percent of root-mean-square difference (PRD). In this paper, given a user-specified PRD, an algorithm is proposed to meet the PRD demand by searching for an appropriate bit rate in an automatic, smooth, and fast manner for the wavelet-based compression. The bit rate searching is modeled as a root-finding problem for a one-dimensional function, where an unknown rate-distortion curve represents the function and the desired rate is the root to be sought. A solution derived from root-finding methods in numerical analysis is proposed. The proposed solution is incorporated in a well-known wavelet-based coding strategy called set partitioning in hierarchical trees. ECG signals taken from the MIT/BIH database are tested, and excellent results in terms of convergence speed, quality variation, and coding performance are obtained.

Algorithms↗
PubMed2006

Wavelet-domain approximation and compression of piecewise smooth images.

The wavelet transform provides a sparse representation for smooth images, enabling efficient approximation and compression using techniques such as zerotrees. Unfortunately, this sparsity does not extend to piecewise smooth images, where edge discontinuities separating smooth regions persist along smooth contours. This lack of sparsity hampers the efficiency of wavelet-based approximation and compression. On the class of images containing smooth C2 regions separated by edges along smooth C2 contours, for example, the asymptotic rate-distortion (R-D) performance of zerotree-based wavelet coding is limited to D(R) (< or = 1/R, well below the optimal rate of 1/R2. In this paper, we develop a geometric modeling framework for wavelets that addresses this shortcoming. The framework can be interpreted either as 1) an extension to the "zerotree model" for wavelet coefficients that explicitly accounts for edge structure at fine scales, or as 2) a new atomic representation that synthesizes images using a sparse combination of wavelets and wedgeprints--anisotropic atoms that are adapted to edge singularities. Our approach enables a new type of quadtree pruning for piecewise smooth images, using zerotrees in uniformly smooth regions and wedgeprints in regions containing geometry. Using this framework, we develop a prototype image coder that has near-optimal asymptotic R-D performance D(R) < or = (log R)2 /R2 for piecewise smooth C2/C2 images. In addition, we extend the algorithm to compress natural images, exploring the practical problems that arise and attaining promising results in terms of mean-square error and visual quality.

Algorithms↗
PubMed1993

ECG data compression by modeling.

The paper presents a novel algorithm for data compression of single lead electrocardiogram (ECG) data. The method is based on parametric modeling of the discrete cosine transformed ECG signal. Improved high frequency reconstruction is achieved by separately modeling the low and the high frequency regions of the transformed signal. Differential pulse code modulation is applied on the model parameters to obtain a further increase in the compression. Compression ratios up to 1:40 were achieved without significant distortion.

Algorithms↗
PubMed1992

ECG data compression by modeling.

This paper presents a novel algorithm for data compression of single lead Electrocardiogram (ECG) data. The method is based on Parametric modeling of the Discrete Cosine Transformed ECG signal. Improved high frequency reconstruction is achieved by separately modeling the low and the high frequency regions of the transformed signal. Differential Pulse Code Modulation is applied on the model parameters to obtain a further increase in the compression. Compression ratios up to 1:40 were achieved without significant distortion.

Algorithms↗
PubMed1994

Improved visualization of stimulated nodules by adaptive enhancement of digital chest radiography.

RATIONALE AND OBJECTIVES: Although digital radiography of the chest has a wide dynamic range, difficulties still remain in visualizing the acquired images faithfully on gray-scale displays (cathode-ray tube [CRT] displays), which have a much lower level of luminance than film view boxes. We propose an adaptive-enhancement algorithm for digital chest radiography that provides faithful visualization of the chest on the CRT. METHODS: We investigated the contrast sensitivity of a CRT monitor and developed an image processing algorithm that compresses the dynamic range and enhances image contrast selectively in the mediastinal area and that transforms the gray scale to visualize the image by use of the full effective dynamic range of the CRT. We performed a receiver-operating characteristic (ROC) study by using simulated nodules to evaluate the clinical value of the proposed algorithm. RESULTS: The processed images provided improved visualization of both mediastinal and lung regions. The area under the ROC curve for retrocardiac or subdiaphragmatic nodule detection increased significantly (from 0.69 to 0.79; P < 0.05). The area under the ROC curve for lung nodule detection also increased (from 0.64 to 0.75; P < 0.1), although not to the level of statistical significance. CONCLUSION: The proposed algorithm allows improved visualization of nodules on digital chest radiographs with the CRT display.

Algorithms↗