6164572
Video quality assessment using structural distortion measurement
Objective image/video quality measures play important roles in various image/video processing applications, such as compression, communication, printing, analysis, registration, restoration and enhancement. Most proposed quality assessment approaches in the literature are error sensitivity-based methods. We follow a new philosophy in designing image/video quality metrics, which uses structural distortion as an estimation of perceived visual distortion. We develop a new approach for video quality assessment. Experiments on the video quality experts group (VQEG) test data set shows that the new quality measure has higher correlation with subjective quality measurement than the proposed methods in VQEG's Phase I tests for full-reference video quality assessment.
207761262
Image quality assessment: from error visibility to structural similarity
Objective methods for assessing perceptual image quality traditionally attempted to quantify the visibility of errors (differences) between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly adapted for extracting structural information from a scene, we introduce an alternative complementary framework for quality assessment based on the degradation of structural information. As a specific example of this concept, we develop a structural similarity index and demonstrate its promise through a set of intuitive examples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000. A MATLAB implementation of the proposed algorithm is available online at http://www.cns.nyu.edu//spl sim/lcv/ssim/.
8060733
Embedded foveation image coding
The human visual system (HVS) is highly space-variant in sampling, coding, processing, and understanding. The spatial resolution of the HVS is highest around the point of fixation (foveation point) and decreases rapidly with increasing eccentricity. By taking advantage of this fact, it is possible to remove considerable high-frequency information redundancy from the peripheral regions and still reconstruct a perceptually good quality image. Great success has been obtained previously by a class of embedded wavelet image coding algorithms, such as the embedded zerotree wavelet (EZW) and the set partitioning in hierarchical trees (SPIHT) algorithms. Embedded wavelet coding not only provides very good compression performance, but also has the property that the bitstream can be truncated at any point and still be decoded to recreate a reasonably good quality image. In this paper, we propose an embedded foveation image coding (EFIC) algorithm, which orders the encoded bitstream to optimize foveated visual quality at arbitrary bit-rates. A foveation-based image quality metric, namely, foveated wavelet image quality index (FWQI), plays an important role in the EFIC system. We also developed a modified SPIHT algorithm to improve the coding efficiency. Experiments show that EFIC integrates foveation filtering with foveated image coding and demonstrates very good coding performance and scalability in terms of foveated image quality measurement.
17056192
Automatic Alignment of High-Resolution NMR Spectra Using a Bayesian Estimation Approach
Nuclear magnetic resonance (NMR) spectral analysis has recently become one of the major means for the detection and recognition of metabolic changes of disease state, physiological alteration, and natural biological variation. For the pattern recognition tasks in which two or more NMR spectra need to be compared, it is critical to properly align the spectra for the subsequent pattern recognition analysis. Previous spectral alignment methods do not consider any baseline intensity variation between the spectra and disregard the effect of noise. Here we formulate the spectra alignment problem in a Bayesian statistical framework, which allows us to simultaneously and efficiently estimate the spectral shift and the baseline intensity variation in the existence of independent additive noise. Experimental results with real high-resolution NMR spectral data from human plasma demonstrate the effectiveness and robustness of the proposed approach
6449041
Adaptive frame prediction for foveation scalable video coding
Embedded rate scalable video coding allows for the extraction of coded visual information at continuously varying bit rates from a single compressed bitstream. This is a very attractive feature for many multimedia communication applications. Motion estimation (ME) /motion compensation (MC) techniques are widely employed in various video coding systems to reduce temporal information redundancy. One of the major challenging problems in ME/MC based rate scalable video coding is how to generate the prediction frame from the previous frame to match the current frame. This problem is more difficult in rate scalable coding than in fixed rate coding because the decoding data rate is unavailable to the encoder. We propose an adaptive frame prediction scheme for foveation scalable video coding (FSVC), which is a new video coding algorithm that combines a foveation-based human visual system (HVS) model with a wavelet-based rate scalable coding algorithm. The new frame prediction algorithm provides an adaptive mechanism to control the prediction errors while reduce error propagation.
5251967
Foveation scalable video coding with automatic fixation selection
Image and video coding is an optimization problem. A successful image and video coding algorithm delivers a good tradeoff between visual quality and other coding performance measures, such as compression, complexity, scalability, robustness, and security. In this paper, we follow two recent trends in image and video coding research. One is to incorporate human visual system (HVS) models to improve the current state-of-the-art of image and video coding algorithms by better exploiting the properties of the intended receiver. The other is to design rate scalable image and video codecs, which allow the extraction of coded visual information at continuously varying bit rates from a single compressed bitstream. Specifically, we propose a foveation scalable video coding (FSVC) algorithm which supplies good quality-compression performance as well as effective rate scalability. The key idea is to organize the encoded bitstream to provide the best decoded video at an arbitrary bit rate in terms of foveated visual quality measurement. A foveation-based HVS model plays an important role in the algorithm. The algorithm is adaptable to different applications, such as knowledge-based video coding and video communications over time-varying, multiuser and interactive networks.
17971442
Exogenous connectors for software components
In existing component models, control originates in components, and connectors are channels for passing on the control to other components. This provides a mechanism for message passing, which allows components to invoke one another's operations by method calls (or remote procedure calls) either directly or indirectly via a channel such as a bus. Thus components in these models mix computation with control, since in performing their computation they also initiate method calls and manage their returns, via connectors. Consequently, in terms of control, components are not loosely coupled. In this paper, we propose exogenous connectors, and demonstrate their use in a small example. In contrast to connectors in existing component models, exogenous connectors initiate calls and manage their returns, and are used to encapsulate control in a component model we are working on. In the example, we demonstrate the feasibility of exogenous connectors, and compare them with connectors in closely related architecture description languages.
33190301
Internet based manufacturing database
Internet Based Manufacturing Database by Shashidhar Iddamsetty Dr Zhiyong Wang, Examination Committee Chair Assistant Professor of Mechanical Engineering University of Nevada, Las Vegas This thesis presents the concept of using distributive databases and World Wide Web as a tool for deploying the Internet based Manufacturing database for insert selection. The rapid phase of development of Internet and its wide usage in the areas of business and Engineering has opened a wide spectrum for the areas of research. This tool is useful in the selection of the cutting inserts for the various machining processes based on the conditions, which a user provides. The Internet based System for Inserts and Parameter selection (ISIPS) has two research databases connected to the Internet, which provides the user with the required machining parameters for Turning or Milling operations. The recommendations provided by this system consist o f the insert types along with the dimensions and the machining parameters feed and speed of cutting. This system has been successfully deployed at University of Nevada, Las Vegas and it can be accessed from the Internet at http://webcutting.nscee.edu.
206639827
OFDM or single-carrier block transmissions?
We compare two block transmission systems over frequency-selective fading channels: orthogonal frequency-division multiplexing (OFDM) versus single-carrier modulated blocks with zero padding (ZP). We first compare their peak-to-average power ratio (PAR) and the corresponding power amplifier backoff for phase-shift keying or quadrature amplitude modulation. Then, we study the effects of carrier frequency offset on their performance and throughput. We further compare the performance and complexity of uncoded and coded transmissions over random dispersive channels, including Rayleigh fading channels, as well as practical HIPERLAN/2 indoor and outdoor channels. We establish that unlike OFDM, uncoded block transmissions with ZP enjoy maximum diversity and coding gains within the class of linearly precoded block transmissions. Analysis and computer simulations confirm the considerable edge of ZP-only in terms of PAR, robustness to carrier frequency offset, and uncoded performance, at the price of slightly increased complexity. In the coded case, ZP is preferable when the code rate is high (e.g., 3/4), while coded OFDM is to be preferred in terms of both performance and complexity when the code rate is low (e.g., 1/2) and the error-correcting capability is enhanced. As ZP block transmissions can approximate serial single-carrier systems as well, the scope of the present comparison is broader.
1450237
An Improved Constructive Neural Network Ensemble Approach to Medical Diagnoses
Neural networks have played an important role in intelligent medical diagnoses. This paper presents an Improved Constructive Neural Network Ensemble (ICNNE) approach to three medical diagnosis problems. New initial structure of the ensemble, new freezing criterion, and a different error function are presented. Experiment results show that our ICNNE approach performed better for most problems.
29035045
Genetic algorithms for determining fuzzy measures from data
A synthetic evaluation of a given object in terms of multiple factors that contribute to some feature of the object (quality, performance, etc.) may be regarded as a system with multiple inputs and one output. Traditionally, the output is expressed as the weighted average of the inputs. Unfortunately, this method is severely limited as it cannot capture any inherent relation among the factors involved. This limitation can be overcome by using the Choquet integral or the fuzzy integral with respect to a fuzzy measure that captures the relation among the factors. The crux of this method is to determine the right fuzzy measure. In this paper, we describe an efficient genetic algorithm for constructing a suitable fuzzy measure from relevant input-output data. This algorithm has a broad applicability in various problem areas, such as decision making, cluster analysis, pattern recognition, image and speech processing, and expert systems.