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Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia Elétrica

ИНТЕЛЛЕКТУАЛЬНЫЙ числовым программным ДЛЯ MIMD-компьютер

For most scientific and engineering problems simulated on computers the solving of problems of the computational mathematics with approximately given initial data constitutes an intermediate or a final stage. Basic problems of the computational mathematics include the investigating and solving of linear algebraic systems, evaluating of eigenvalues and eigenvectors of matrices, the solving of systems of non-linear equations, numerical integration of initial- value problems for systems of ordinary differential equations.Для більшості наукових та інженерних задач моделювання на ЕОМ рішення задач обчислювальної математики з наближено заданими вихідними даними складає проміжний або остаточний етап. Основні проблеми обчислювальної математики відносяться дослідження і рішення лінійних алгебраїчних систем оцінки власних значень і власних векторів матриць, рішення систем нелінійних рівнянь, чисельного інтегрування початково задач для систем звичайних диференціальних рівнянь.Для большинства научных и инженерных задач моделирования на ЭВМ решение задач вычислительной математики с приближенно заданным исходным данным составляет промежуточный или окончательный этап. Основные проблемы вычислительной математики относятся исследования и решения линейных алгебраических систем оценки собственных значений и собственных векторов матриц, решение систем нелинейных уравнений, численного интегрирования начально задач для систем обыкновенных дифференциальных уравнений

Application and Theory of Multimedia Signal Processing Using Machine Learning or Advanced Methods

This Special Issue is a book composed by collecting documents published through peer review on the research of various advanced technologies related to applications and theories of signal processing for multimedia systems using ML or advanced methods. Multimedia signals include image, video, audio, character recognition and optimization of communication channels for networks. The specific contents included in this book are data hiding, encryption, object detection, image classification, and character recognition. Academics and colleagues who are interested in these topics will find it interesting to read

INFORMATION THEORETIC CRITERIA FOR IMAGE QUALITY ASSESSMENT BASED ON NATURAL SCENE STATISTICS

Measurement of visual quality is crucial for various image and video processing applications. It is widely applied in image acquisition, media transmission, video compression, image/video restoration, etc. The goal of image quality assessment (QA) is to develop a computable quality metric which is able to properly evaluate image quality. The primary criterion is better QA consistency with human judgment. Computational complexity and resource limitations are also concerns in a successful QA design. Many methods have been proposed up to now. At the beginning, quality measurements were directly taken from simple distance measurements, which refer to mathematically signal fidelity, such as mean squared error or Minkowsky distance. Lately, QA was extended to color space and the Fourier domain in which images are better represented. Some existing methods also consider the adaptive ability of human vision. Unfortunately, the Video Quality Experts Group indicated that none of the more sophisticated metrics showed any great advantage over other existing metrics. This thesis proposes a general approach to the QA problem by evaluating image information entropy. An information theoretic model for the human visual system is proposed and an information theoretic solution is presented to derive the proper settings. The quality metric is validated by five subjective databases from different research labs. The key points for a successful quality metric are investigated. During the testing, our quality metric exhibits excellent consistency with the human judgments and compatibility with different databases. Other than full reference quality assessment metric, blind quality assessment metrics are also proposed. In order to predict quality without a reference image, two concepts are introduced which quantitatively describe the inter-scale dependency under a multi-resolution framework. Based on the success of the full reference quality metric, several blind quality metrics are proposed for five different types of distortions in the subjective databases. Our blind metrics outperform all existing blind metrics and also are able to deal with some distortions which have not been investigated