The University of Sydney

Massachusetts General Hospital Corporation

Mitsubishi Electric Research Labs.

Ling Guan

Anthony Vetro

Sun-Yuan Kung

Min Wu

Jeffrey P Sutton

Hau-San Wong

Robert A Joyce

A method for dynamically allocating network resources while transferring multimedia at variable bit-rates in a network extracts first content features from the multimedia to determine renegotiation points and observation periods. Second content features and traffic features are extracted from the multimedia bit stream during the observation periods. The second content features and the traffic features are combined in a neural network to predict the network resources to be allocated at the renegotiation points.

Dynamic network resource allocation using multimedia content features and traffic features

A regularization system and method for image restoration in homogeneous or inhomogeneous environments. The system and method includes features similar to a neural network with intermediate levels of structure including a pixel having processing capabilities; clusters consisting of a plurality of interconnected pixels and also having processing capabilities; and an image space comprised of a plurality of interconnected pixels and clusters and also having processing capabilities. The system and method also include means for assigning a regularization parameter to each pixel depending on the local variance of intensity of pixels; decomposing the image space into clusters of pixels, each cluster having the same regularization parameter; imposing a blurring function on each pixel; rapidly forming a regularized image by simultaneous local and global encoding of a regularization matrix onto each pixel directed through a process of gradient energy decent; and a means of assessing the output image.

System and method for image regularization in inhomogeneous environments

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Bexley North, Australia

Ling Guan