Biomedical subjects

Yucel Altunbasak

Publications and source records attributed to Yucel Altunbasak.

5 recordsLinked to original sources

PubMed2006

Protein secondary structure prediction for a single-sequence using hidden semi-Markov models.

BACKGROUND: The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algorithms: Single-sequence prediction algorithms imply that information about other (homologous) proteins is not available, while algorithms of the second type imply that information about homologous proteins is available, and use it intensively. The single-sequence algorithms could make an important contribution to studies of proteins with no detected homologs, however the accuracy of protein secondary structure prediction from a single-sequence is not as high as when the additional evolutionary information is present. RESULTS: In this paper, we further refine and extend the hidden semi-Markov model (HSMM) initially considered in the BSPSS algorithm. We introduce an improved residue dependency model by considering the patterns of statistically significant amino acid correlation at structural segment borders. We also derive models that specialize on different sections of the dependency structure and incorporate them into HSMM. In addition, we implement an iterative training method to refine estimates of HSMM parameters. The three-state-per-residue accuracy and other accuracy measures of the new method, IPSSP, are shown to be comparable or better than ones for BSPSS as well as for PSIPRED, tested under the single-sequence condition. CONCLUSIONS: We have shown that new dependency models and training methods bring further improvements to single-sequence protein secondary structure prediction. The results are obtained under cross-validation conditions using a dataset with no pair of sequences having significant sequence similarity. As new sequences are added to the database it is possible to augment the dependency structure and obtain even higher accuracy. Current and future advances should contribute to the improvement of function prediction for orphan proteins inscrutable to current similarity search methods.

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PubMed2005

Distributed video streaming using multiple description coding and unequal error protection.

This paper presents a distributed video streaming framework using unbalanced multiple description coding (MDC) and unequal error protection. In the proposed video streaming framework, two senders simultaneously stream complementary descriptions to a single receiver over different paths. To minimize the overall distortion and exploit the benefits of multipath transport when the characteristics of each path are different, an unbalanced MDC method for wavelet-based coders combined with a TCP-friendly rate allocation algorithm is proposed. The proposed rate allocation algorithm adjusts the transmission rates and the channel coding rates for all senders in a coordinated fashion to minimize the overall distortion. Simulation results show that the proposed unbalanced MDC combined with our rate allocation algorithm achieves about 1-6 dB higher peal signal-to-noise ratio compared to conventional balanced MDC when the available bandwidths along the two paths are different under time-varying network conditions.

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PubMed2005

Super-resolution reconstruction of hyperspectral images.

Hyperspectral images are used for aerial and space imagery applications, including target detection, tracking, agricultural, and natural resource exploration. Unfortunately, atmospheric scattering, secondary illumination, changing viewing angles, and sensor noise degrade the quality of these images. Improving their resolution has a high payoff, but applying super-resolution techniques separately to every spectral band is problematic for two main reasons. First, the number of spectral bands can be in the hundreds, which increases the computational load excessively. Second, considering the bands separately does not make use of the information that is present across them. Furthermore, separate band super-resolution does not make use of the inherent low dimensionality of the spectral data, which can effectively be used to improve the robustness against noise. In this paper, we introduce a novel super-resolution method for hyperspectral images. An integral part of our work is to model the hyperspectral image acquisition process. We propose a model that enables us to represent the hyperspectral observations from different wavelengths as weighted linear combinations of a small number of basis image planes. Then, a method for applying super resolution to hyperspectral images using this model is presented. The method fuses information from multiple observations and spectral bands to improve spatial resolution and reconstruct the spectrum of the observed scene as a combination of a small number of spectral basis functions.

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PubMed2004

Super-resolution reconstruction of compressed video using transform-domain statistics.

Considerable attention has been directed to the problem of producing high-resolution video and still images from multiple low-resolution images. This multiframe reconstruction, also known as super-resolution reconstruction, is beginning to be applied to compressed video. Super-resolution techniques that have been designed for raw (i.e., uncompressed) video may not be effective when applied to compressed video because they do not incorporate the compression process into their models. The compression process introduces quantization error, which is the dominant source of error in some cases. In this paper, we propose a stochastic framework where quantization information as well as other statistical information about additive noise and image prior can be utilized effectively.

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PubMed2004

A multiple-substream unequal error-protection and error-concealment algorithm for SPIHT-coded video bitstreams.

This paper presents a coordinated multiple-substream unequal error-protection and error-concealment algorithm for SPIHT-coded bitstreams transmitted over lossy channels. In the proposed scheme, we divide the video sequence corresponding to a group of pictures into two subsequences and independently encode each subsequence using a three-dimensional SPIHT algorithm. We use two different partitioning schemes to generate the substreams, each of which offers some advantages under the appropriate channel condition. Each substream is protected by an FEC-based unequal error-protection algorithm, which assigns unequal forward error correction codes to each bit plane. Any information that is lost during the transmission for any substream is estimated at the receiver by using the correlation between the substreams and the smoothness of the video signal. Simulation results show that the proposed multiple-substream UEP algorithm is simple, fast, and robust in hostile network conditions, and that the proposed error-concealment algorithm can achieve 2-3-dB PSNR gain over the case when error concealment is not used at high packet-loss rates.

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