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A wavelet-based two-stage near-lossless coder.

In this paper, we present a two-stage near-lossless compression scheme. It belongs to the class of "lossy plus residual coding" and consists of a wavelet-based lossy layer followed by arithmetic coding of the quantized residual to guarantee a given L(infinity) error bound in the pixel domain. We focus on the selection of the optimum bit rate for the lossy layer to achieve the minimum total bit rate. Unlike other similar lossy plus lossless approaches using a wavelet-based lossy layer, the proposed method does not require iteration of decoding and inverse discrete wavelet transform in succession to locate the optimum bit rate. We propose a simple method to estimate the optimal bit rate, with a theoretical justification based on the critical rate argument from the rate-distortion theory and the independence of the residual error.

Algorithms↗

Arbitrary waveform coded excitation using bipolar square wave pulsers in medical ultrasound.

This paper presents a new coded excitation scheme that efficiently synthesizes codes for arbitrary waveforms using a bipolar square wave pulser. In a coded excitation system, pulse compression is performed to restore the axial resolution. In order to maintain low range sidelobes, the system needs to transmit signals that have smooth spectra. However, such a transmitter requires the generation of arbitrary waveforms and, therefore, is more expensive. In other words, a trade-off is necessary between the compression performance and the transmitter cost. Here we propose a method that preserves the low-cost advantage of a bipolar pulser while achieving approximately the same compression performance as an arbitrary waveform generator. The key idea of the proposed method is the conversion of a nonbinary code (i.e., requiring an arbitrary waveform generator) with good compression performance into a binary code (i.e., requiring only a bipolar pulser) by code translation and code tuning. The code translation is implemented by sending the nonbinary code into a virtual one-bit, sigma-delta modulator, and the code tuning involves minimizing the root-mean-square error between the resultant binary code and the original nonbinary code by sequential and iterative tuning while taking the transducer response into account. Tukey-windowed chirps are known to have good compression performance. Such chirps of different durations (16, 20, and 24 micros), all with a taper ratio of 0.15, a center frequency of 2.5 MHz, and an equivalent bandwidth of 1.5 MHz, were converted into binary Tukey-windowed chirps that were compared with pseudochirps (i.e., direct binary approximations of the original chirp) over the same spectral band. The bit rate was 40 MHz. Simulation results show that the use of binary Tukey-windowed chirps can reduce the code duration by 20.6% or the peak sidelobe level by 6 dB compared to the commonly used pseudochirps. Experimental results obtained under the same settings were in agreement with the simulations. Our results demonstrate that arbitrary waveform coded excitation can be realized using bipolar square wave pulsers for applications in medical ultrasound.

Algorithms↗

On the use of PRD and CR parameters for ECG compression.

The quality measurement of the reconstructed signal in an electrocardiogram (ECG) compression scheme must be obtained by objective means being the percentage root-mean-square difference (PRD) the most widely used. However, this parameter is dependent on the dc level so that confusion can be stated in the evaluation of ECG compressors. In this communication, it will be shown that if the performance of an ECG coder is evaluated only in terms of quality, considering exclusively the PRD parameter, incorrect conclusions can be inferred. The objective of this work is to propose the joint use of several parameters, as simulations will show, effectiveness and performance of the ECG coder are evaluated with more precision, and the way of inferring conclusions from the obtained results is more reliable.

Algorithms↗

Embedded multiple description coding of video.

Real-time delivery of video over best-effort error-prone packet networks requires scalable erasure-resilient compression systems in order to 1) meet the users' requirements in terms of quality, resolution, and frame-rate; 2) dynamically adapt the rate to the available channel capacity; and 3) provide robustness to data losses, as retransmission is often impractical. Furthermore, the employed erasure-resilience mechanisms should be scalable in order to adapt the degree of resiliency against transmission errors to the varying channel conditions. Driven by these constraints, we propose in this paper a novel design for scalable erasure-resilient video coding that couples the compression efficiency of the open-loop architecture with the robustness provided by multiple description coding. In our approach, scalability and packet-erasure resilience are jointly provided via embedded multiple description scalar quantization. Furthermore, a novel channel-aware rate-allocation technique is proposed that allows for shaping on-the-fly the output bit rate and the degree of resiliency without resorting to channel coding. As a result, robustness to data losses is traded for better visual quality when transmission occurs over reliable channels, while erasure resilience is introduced when noisy links are involved. Numerical results clearly demonstrate the advantages of the proposed approach over equivalent codec instantiations employing 1) no erasure-resilience mechanisms, 2) erasure-resilience with nonscalable redundancy, or 3) data-partitioning principles.

Algorithms↗

Image enhancement in the JPEG domain for people with vision impairment.

An image enhancement algorithm for low-vision patients was developed for images compressed using the JPEG standard. The proposed algorithm enhances the images in the discrete cosine transform domain by weighting the quantization table in the decoder. Our specific implementation increases the contrast at all bands of frequencies by an equal factor. The enhancement algorithm has four advantages: 1) low computational cost; 2) suitability for real-time application; 3) ease of adjustment by end-users (for example, adjusting a single parameter); and 4) less severe block artifacts as compared with conventional (post compression) enhancements. Experiments with visually impaired patients show improved perceived image quality at moderate levels of enhancement but rejection of artifacts caused by higher levels of enhancement.

Algorithms↗

SIMPLISMA and ALS applied to two-way nonlinear wavelet compressed ion mobility spectra of chemical warfare agent simulants.

Ion mobility spectrometry is a rapid scanning measurement method for which compression methods that facilitate the handling of large collections of data are beneficial. Peak distortion in reconstructed ion mobility spectra from linear wavelet compression is problematic in that artifact peaks may cause false positive alarms. Peak shifting also may cause false alarms if target peaks shift out of or interfering peaks shift into detection windows. Nonlinear wavelet compression (NLWC) preserves peak shape and can lessen the degree of distortion, shifting, and artifact peaks in the reconstructed spectra. NLWC was applied to achieve high compression and fidelity in the reconstructed spectra. Another benefit is that NLWC improves signal-to-noise ratios and thus the models built from compressed data are improved. By compressing both the drift time order and the spectrum acquisition order, greater compressions maybe achieved. A two-way nonlinear wavelet compression method that incorporates alternating least squares (2W-NLWC-ALS) algorithm was devised by applying ALS to partially reconstructed wavelet coefficients generated from two-way NLWC. The number of components in a data set can be determined automatically using ASIMPLISMA. The smaller ALS models are saved as the final compressed data and can be used to reconstruct the entire data set efficiently without maintaining the compressed wavelet coefficient matrix of the original data set. The 2W-NLWC-ALS algorithm provides greater compression ratios compared to regular wavelet compression and interpretable models. Using this method, large volumes of data can be acquired and easily evaluated through a simple compressed model. A compression ratio of 510 ppm, root-mean-square error (E(RMS)) of 6.3 mV (full-scale signal is usually 1 V or larger), and relative root-mean-square error (RE(RMS)) of 1.62% were achieved for data sets collected by CAM. A compression ratio of 46 ppm, E(RMS) of 9.2 mV, and RE(RMS) of 0.42% were achieved for data sets collected with an ITEMISER instrument. The 2W-NLWC-ALS algorithm is an efficient compression method that provides the benefits of a simple model.

Algorithms↗

Liquid boundary movements in cylindrical and convex hydrophobic matrix tablets: Effects on tablet cracking and drug release.

The aim of this study was to investigate liquid penetration into both cylindrical and convex hydrophobic matrix tablets and to relate the changes in tablet structure to drug release. Starch acetate with degree of substitution of 2.7 was used as a hydrophobic matrix former and anhydrous caffeine as a freely soluble model drug. Phenolred was used as a colouring agent to enhance the visual detection of the liquid boundary movements, which were examined in axial and radial directions for both types of tablets. The tablets started to expand during the dissolution, resulting in cracking as the liquid boundary penetrated into tablet. The cracking influences drug release by shortening the diffusion path and decreasing the tortuosity. The liquid boundaries proceed differently in cylindrical and convex tablets, this being attributable to differences in pore structure and density distribution. Cylindrical tablets are quite homogeneous in terms of density, but convex tablets have more porous areas at the domes of the tablet.

Algorithms↗

High frame rate ultrasonic imaging system based on the angular spectrum principle.

A kind of high frame rate (HFR) 2D and 3D imaging method was developed by Jianyu Lu in 1997. Because only one transmission is required to construct a frame of image, this method can reach an ultra high frame rate (about 3750 volumes or frames per second for biological soft tissues at a depth of 200 mm). In this paper, a new HFR method is presented in the view of angular spectrum. Compared with conventional dynamic focusing method which uses delay-and-sum processing, and Lu's HFR method which uses a kind of special weighting on the received signal, the new method only uses the Fourier transform algorithm to construct image. So the system implementation of the method could be greatly simplified. During constructing image, several array beams with different parameter are used as transmitted signal, and the spectrum of a frame of image is obtained by synthesizing the image spectrums related to different transmit event. The simulation result shows that the solution not only suppresses the sidelobe of system greatly and obtains the high quality image, but also still keeps high frame rate to some extent.

Algorithms↗

Study on application of complementary Golay code into high frame rate ultrasonic imaging system.

The high frame rate (HFR) ultrasonic imaging system, which is developed with limited diffraction beams, constructs images at a high frame rate. However the rectangular imaging area, to some extent, restricts the far field imaging information. At the same time, by virtue of one transmission event for constructing image, the system suffers from low SNR. In this paper we present a computationally efficient method to construct sector mode image and to increase the SNR in HFR system. The method uses orthogonal complementary Golay coded excitation to realize two transmit and receive events. Each emission simultaneously transmits two plane waves with different transmission angle. Then according to Golay code orthogonality, the received echo signals related to different angles are isolated and used to construct two images of different imaging area by HFR method. Finally the two images are synthesized to one frame of sector mode image.

Algorithms↗

On Maxwell's demons and the origin of evolutionary variations: an internalist perspective.

This paper defends an internalist perspective of selection based on the hypothesis that considers living evolutionary units as Maxwell's demons (MD) or Zurek's Information Gathering and Using Systems (IGUS). Individuals are considered as IGUS that extract work by means of measuring and recording processes. Interactions or measurements convert uncertainty about the environment (Shannon's information, H) into internalized information in the form of a compressed record (Chaitin's algorithmic complexity, K). The requirements of the model and the limitations inherent to its formalization are discussed. This approach offers an alternative view to the causes of evolutionary variations which goes beyond the classical Lamarckian-Darwinian controversy. I argue that random variations only apply near-to-equilibrium at the time organisms have attained structural closure, and that a speed up of mutation rates that facilitates the production of directed variations occurs far-from-equilibrium due to organisms' openness to the surrounding conditions. However, real organisms are located somewhere between the above two cases and thus, operate at an intermediate stage where there is a maximum efficiency of H/K conversion. In consequence, IGUS keep their autonomy and evolving capacity by compromising between external circumstances and inner constraints. This compromise is made possible by closure regulation. Likewise, this model explains why nature has favored the selection of agents capable of selectively recording a partial description of their environment.

Biological Evolution↗

MinSet: a general approach to derive maximally representative database subsets by using fragment dictionaries and its application to the SCOP database.

MOTIVATION: The size of current protein databases is a challenge for many Bioinformatics applications, both in terms of processing speed and information redundancy. It may be therefore desirable to efficiently reduce the database of interest to a maximally representative subset. RESULTS: The MinSet method employs a combination of a Suffix Tree and a Genetic Algorithm for the generation, selection and assessment of database subsets. The approach is generally applicable to any type of string-encoded data, allowing for a drastic reduction of the database size whilst retaining most of the information contained in the original set. We demonstrate the performance of the method on a database of protein domain structures encoded as strings. We used the SCOP40 domain database by translating protein structures into character strings by means of a structural alphabet and by extracting optimized subsets according to an entropy score that is based on a constant-length fragment dictionary. Therefore, optimized subsets are maximally representative for the distribution and range of local structures. Subsets containing only 10% of the SCOP structure classes show a coverage of >90% for fragments of length 1-4. AVAILABILITY: http://mathbio.nimr.mrc.ac.uk/~jkleinj/MinSet. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Algorithms↗

Context-tree modeling of observed symbolic dynamics.

Modern techniques invented for data compression provide efficient automated algorithms for the modeling of the observed symbolic dynamics. We demonstrate the relationship between coding and modeling, motivating the well-known minimum description length (MDL) principle, and give concrete demonstrations of the "context-tree weighting" and "context-tree maximizing" algorithms. The predictive modeling technique obviates many of the technical difficulties traditionally associated with the correct MDL analyses. These symbolic models, representing the symbol generating process as a finite-state automaton with probabilistic emission probabilities, provide excellent and reliable entropy estimations. The resimulations of estimated tree models satisfying the MDL model-selection criterion are faithful to the original in a number of measures. The modeling suggests that the automated context-tree model construction could replace fixed-order word lengths in many traditional forms of empirical symbolic analysis of the data. We provide an explicit pseudocode for implementation of the context-tree weighting and maximizing algorithms, as well as for the conversion to an equivalent Markov chain.

Journal Article↗

Complete and flexible replacement of chaotic uncertainty with transmitted information.

Natural chaos can be described as an information source emitting symbolic sequences with positive entropy. We use two algorithmic techniques from data compression in a nonstandard way along with a control scheme to replace the natural uncertainty in chaotic systems with an arbitrary digital message. Unlike previous targeting-based control, the controlled, deterministic, transmission appears statistically identical to natural chaos, with a message modulated on it at the intrinsic Kolmogorov-Sinai information generation rate of the chaotic oscillator. Thus, chaotic communication by targeting need not consume any additional channel capacity beyond that required by the message itself and the message-bearing signal may appear identical to the uncontrolled oscillator. We also demonstrate control and data transmission at the channel capacity of the oscillator, the maximum possible data rate compatible with the grammar.

Journal Article↗

Spatial shape error concealment for object-based image and video coding.

In this paper, an original spatial shape error-concealment technique, to be used in the context of object-based image and video coding schemes, is proposed. In this technique, it is assumed that the shape of the corrupted object at hand is in the form of a binary alpha plane, in which some of the shape data is missing due to channel errors. From this alpha plane, a contour corresponding to the border of the object can be extracted. However, due to errors, some parts of the contour will be missing and, therefore, the contour will be broken. The proposed technique relies on the interpolation of the missing contours with Bézier curves, which is done based on the available surrounding contours. After all the missing parts of the contour have been interpolated, the concealed alpha plane can be easily reconstructed from the fully recovered contour and used instead of the erroneous one improving the final subjective impact.

Algorithms↗

Adaptive shape and texture intra refreshment schemes for improved error resilience in object-based video coding.

Video encoders may use several techniques to improve error resilience. In particular, for video encoders that rely on predictive (inter) coding to remove temporal redundancy, intra coding refreshment is especially useful to stop temporal error propagation when errors occur in the transmission or storage of the coded streams, since these errors may cause the decoded quality to decay very rapidly. In the context of object-based video coding, intra coding refreshment can be applied to both the shape and texture data. In this paper, novel shape and texture intra refreshment schemes are proposed which can be used by object-based video encoders, such as MPEG-4 video encoders, independently or combined. These schemes allow to adaptively determine when the shape and texture of the various video objects in a scene should be refreshed in order to maximize the decoded video quality for a certain total bit rate.

Algorithms↗

Adaptively quadratic (AQua) image interpolation.

Image interpolation is a key aspect of digital image processing. This paper presents a novel interpolation method based on optimal recovery and adaptively determining the quadratic signal class from the local image behavior. The advantages of the new interpolation method are the ability to interpolate directly by any factor and to model properties of the data acquisition system into the algorithm itself. Through comparisons with other algorithms it is shown that the new interpolation is not only mathematically optimal with respect to the underlying image model, but visually it is very efficient at reducing jagged edges, a place where most other interpolation algorithms fail.

Algorithms↗

Efficient implementation of accurate geometric transformations for 2-D and 3-D image processing.

This paper proposes the use of a polynomial interpolator structure (based on Horner's scheme) which is efficiently realizable in hardware, for high-quality geometric transformation of two- and three-dimensional images. Polynomial-based interpolators such as cubic B-splines and optimal interpolators of shortest support are shown to be exactly implementable in the Horner structure framework. This structure suggests a hardware/software partition which can lead to efficient implementations for multidimensional interpolation.

Algorithms↗

Quality-aware images.

We propose the concept of quality-aware image, in which certain extracted features of the original (high-quality) image are embedded into the image data as invisible hidden messages. When a distorted version of such an image is received, users can decode the hidden messages and use them to provide an objective measure of the quality of the distorted image. To demonstrate the idea, we build a practical quality-aware image encoding, decoding and quality analysis system, which employs: 1) a novel reduced-reference image quality assessment algorithm based on a statistical model of natural images and 2) a previously developed quantization watermarking-based data hiding technique in the wavelet transform domain.

Algorithms↗