Dimitris Anastassiou

Performance models of statistical multiplexing in packet video communications

Models and results are presented that assess the performance of statistical multiplexing of independent video sources. Presented results indicate that the probability of buffering (or delaying) video data beyond an acceptable limit drops dramatically as the number of multiplexed sources increases beyond one. This demonstrates that statistical or asynchronous time-division multiplexing (TDM) can efficiently absorb temporal variations of the bit rate of individual sources without the significant variations in reception quality exhibited by multimode videocoders for synchronous TDM or circuit-switched transmission. Two source models are presented. The first model is an autoregressive continuous-state, discrete-time Markov process, which was used to generate source data in simulation experiments. The second model is a discrete-state, continuous-time Markov process that was used in deriving a fluid-flow queuing analysis. The presented study shows that both models generated consistent numerical results in terms of queuing performance. >

Subpixel edge localization and the interpolation of still images

In this paper, we present a nonlinear interpolation scheme for still image resolution enhancement. The algorithm is based on a source model emphasizing the visual integrity of detected edges and incorporates a novel edge fitting operator that has been developed for this application. A small neighborhood about each pixel in the low-resolution image is first mapped to a best-fit continuous space step edge. The bilevel approximation serves as a local template on which the higher resolution sampling grid can then be superimposed (where disputed values in regions of local window overlap are averaged to smooth errors). The result is an image of increased resolution with noticeably sharper edges and, in all tried cases, lower mean-squared reconstruction error than that produced by linear techniques.

Genomic signal processing

Genomics is a highly cross-disciplinary field that creates paradigm shifts in such diverse areas as medicine and agriculture. It is believed that many significant scientific and technological endeavors in the 21st century will be related to the processing and interpretation of the vast information that is currently revealed from sequencing the genomes of many living organisms, including humans. Genomic information is digital in a very real sense; it is represented in the form of sequences of which each element can be one out of a finite number of entities. Such sequences, like DNA and proteins, have been mathematically represented by character strings, in which each character is a letter of an alphabet. In the case of DNA, the alphabet is size 4 and consists of the letters A, T, C and G; in the case of proteins, the size of the corresponding alphabet is 20. As the list of references shows, biomolecular sequence analysis has already been a major research topic among computer scientists, physicists, and mathematicians. The main reason that the field of signal processing does not yet have significant impact in the field is because it deals with numerical sequences rather than character strings. However, if we properly map a character string into, one or more numerical sequences, then digital signal processing (DSP) provides a set of novel and useful tools for solving highly relevant problems. For example, in the form of local texture, color spectrograms visually provide significant information about biomolecular sequences which facilitates understanding of local nature, structure, and function. Furthermore, both the magnitude and the phase of properly defined Fourier transforms can be used to predict important features like the location and certain properties of protein coding regions in DNA. Even the process of mapping DNA into proteins and the interdependence of the two kinds of sequences can be analyzed using simulations based on digital filtering. These and other DSP-based approaches result in alternative mathematical formulations and may provide improved computational techniques for the solution of useful problems in genomic information science and technology.

Models for packet switching of variable-bit-rate video sources

The authors extend earlier work (ibid., vol.36, p.834-44, Jul. 1988) in modeling video sources using interframe coding schemes and in carrying out buffer queueing analysis for the multiplexing of several such sources. The previous models and analysis were suitable for relatively uniform activity scenes. Here, models are considered for scenes with multiple activity levels which lead to sudden changes in the coder output bit rates. Such models apply to talker-listener alternating scenes, as well as to situations where there is a mix of dissimilar services, e.g., television and videotelephony. Correlated Markov models for the corresponding sources are given. A flow-equivalent queueing analysis is used to obtain common buffer queue distributions and probabilities of packet loss. The results demonstrate the efficiency of packet video on a single link, due to the smoothing effect of multiplexing several variable-bit-rate video sources. >

Computational Analysis Of The Synergy Among Multiple Interacting Factors

Diseases such as cancer are often related to collaborative effects involving interactions of multiple genes within complex pathways, or to combinations of multiple SNPs. To understand the structure of such mechanisms, it is helpful to analyze genes in terms of the purely cooperative, as opposed to independent, nature of their contributions towards a phenotype. Here, we present an information‐theoretic analysis that provides a quantitative measure of the multivariate synergy and decomposes sets of genes into submodules each of which contains synergistically interacting genes. When the resulting computational tools are used for the analysis of gene expression or SNP data, this systems‐based methodology provides insight into the biological mechanisms responsible for disease.

Constrained and general dynamic rate shaping of compressed digital video

We introduce the concept of dynamic rate shaping, a technique to adapt the rate of compressed video bitstreams (MPEG-1, MPEG-2, H.261, as well as JPEG) to dynamically varying bit rate constraints. The approach provides an interface (or filter) between the encoder and the network, with which the encoders output can be perfectly matched to the networks quality of service characteristics. Since the presented algorithms do not require interaction with the encoder, they are fully applicable to precoded, stored video (e.g., video-on-demand systems). By decoupling the encoder and the network, universal interoperability can be achieved. In essence, DRS bridges the gap between CBR and VBR video, allowing a continuum of possibilities between the two. A set of low-complexity algorithms for so-called unconstrained dynamic rate shaping are presented, and both optimal and extremely fast designs are discussed. Experimental results are provided using actual MPEG-2 bitstreams.

Meeting Arbitrary QoS Constraints Using Dynamic Rate Shaping of Coded Digital Video

We introduce the concept of Dynamic Rate Shaping, a technique to adapt the rate of compressed video bitstreams (MPEG-1, MPEG-2, H.261, as well as JPEG) to dynamically varying rate (and delay) constraints. The approach provides an interface (or filter) between the encoder and the network, with which the encoders output can be perfectly matched to the networks quality of service characteristics. Since the presented algorithms do not require interaction with the encoder, they are fully applicable to precoded, stored video (as in, for example, video-on-demand systems). By providing decoupling of the encoder and the network, universal interoperability can be achieved. A set of lowcomplexity algorithms for dynamic rate shaping is presented, and both optimal and extremely fast designs are discussed. The latter are simple enough to allow software-based implementation. Experimental results are provided using actual MPEG-2 bitstreams.

Minimal error drift in frequency scalability for motion-compensated DCT coding

The authors mathematically analyze the drift of low-resolution images obtained from a smaller IDCT of a subset of the DCT coefficients of the full-resolution images in motion-compensated hybrid predictive/DCT coding such as MPEG-2, which allows for frequency scalability. Using this mathematical structure, they derive a low-resolution decoder that has the theoretically minimum possible drift, and propose techniques for implementation that produce substantial improvement in real sequences. The minimum drift can also be used as a milestone, to be compared with other techniques of drift reduction (of worse performance but lower complexity). For the case where leakage is used to reduce the drift, the authors determine a minimum-energy non-uniform DCT-domain leakage matrix which is no more complex than uniform leakage, but gives a substantial improvement. Finally, they note that DCT-based pyramidal coding is essentially the same as the drift case, and thus they use the same mathematical structure to derive the theoretically-best upward predictor in pyramidal coding. >

Biomolecular events in cancer revealed by attractor metagenes

Mining gene expression profiles has proven valuable for identifying signatures serving as surrogates of cancer phenotypes. However, the similarities of such signatures across different cancer types have not been strong enough to conclude that they represent a universal biological mechanism shared among multiple cancer types. Here we present a computational method for generating signatures using an iterative process that converges to one of several precise attractors defining signatures representing biomolecular events, such as cell transdifferentiation or the presence of an amplicon. By analyzing rich gene expression datasets from different cancer types, we identified several such biomolecular events, some of which are universally present in all tested cancer types in nearly identical form. Although the method is unsupervised, we show that it often leads to attractors with strong phenotypic associations. We present several such multi-cancer attractors, focusing on three that are prominent and sharply defined in all cases: a mesenchymal transition attractor strongly associated with tumor stage, a mitotic chromosomal instability attractor strongly associated with tumor grade, and a lymphocyte-specific attractor.

Time-recursive deinterlacing for IDTV and pyramid coding

Most improved-definition television (IDTV) receivers use progressive scanning to reduce artifacts associated with interlacing (e.g. interline flicker, line crawl). Some novel techniques of motion compensated interpolation of the missing lines of interlaced monochrome and color sequences, reducing the artifacts associated with interlacing, and effectively increasing the vertical resolution of the image sequences are proposed. Time-recursive motion compensation prediction is introduced, in which all previously displayed history (not just the previous field) is used to predict the missing pixel values. The next future field is also used for the same purpose, by a lookahead scheme. Motion estimation is done using a quadtree-based segmented block-matching technique with half-pixel accuracy. To avoid artifacts and obtain full resolution in still regions, such as background, motion adaptation is also used. How to apply this algorithm to pyramid coding to achieve a better compression rate and compatibility with other lesser resolution standards is discussed. >