15360768
A hardware/software reconfigurable architecture for adaptive wireless image communication
With the projected significant growth in mobile internet and multimedia services, there is a strong demand for next-generation appliances capable of wireless image communication. One of the major bottlenecks in enabling wireless image communication is the high energy requirement, which may surpass the current and future capabilities of battery technologies. Past studies have shown that the bottlenecks can be overcome by developing adaptive multimedia compression algorithms which can adapt to dynamic channel conditions and service requirements. We present an application-specific hardware/software reconfigurable architecture to support adaptive image compression algorithms. We present a design methodology which considers co-design between adaptive algorithms and architectural design leading to a reconfigurable architecture for image compression algorithms. Codesign of the proposed architecture aims not only at performance and power efficient implementation, but also towards fast and efficient run-time adaptation of an adaptive image compression algorithm.
17626745
Design of an Adaptive Architecture for Energy Efficient Wireless Image Communication
With the projected significant growth in mobile internet and multimedia services, there is a strong demand for next-generation wireless appliances capable of image communication. However, wireless image communication faces significant bottlenecks including high energy and bandwidth consumption. Past studies have shown that the bottlenecks to wireless image communication can be overcome by developing adaptive image compression algorithms and dynamically adapting them to current channel conditions and service requirements [1,2].In this paper, we present the design of an adaptive hardware/software architecture that enables adaptive wireless image communication. Through intelligent co-design of the proposed architecture and algorithms, we achieve an architecture which enables not only power and performance efficient implementation, but also fast and efficient run-time adaptation of image compression parameters. To achieve efficient image compression and run-time adaptation, we characterized the adaptation needs of an adaptive image compression algorithm in terms of parameters, and implemented an adaptive hardware/software architecture capable of executing JPEC image compression with different parameters. We present experimental results demonstrating that the proposed architecture enables low overhead adaptation to current wireless conditions and requirements while implementing a low cost (energy and performance) implementation of adaptive image compression algorithms.
1277199
Modeling and minimization of interconnect energy dissipation in nanometer technologies
As the technology sizes of semiconductor devices continue to decrease, the effect of nanometer technologies on interconnects, such as crosstalk glitches and timing variations, become more significant. In this paper, we study the effect of nanometer technologies on energy dissipation in interconnects. We propose a new power estimation technique which considers DSM effects, resulting in significantly more accurate energy dissipation estimates than transition-count based methods for on-chip interconnects. We also introduce an energy minimization technique which attempts to minimize large voltage swings across the cross-coupling capacitances between interconnects. Even though the number of transitions may increase, our method yields a decrease in power consumption of up to 50%.
6301159
The Image Fidelity Assessor
In this paper we describe the Image Fidelity Assessor (IFA), a model of the human visual system designed to evaluate perceived fidelity. In particular, we describe the structure of the model, present results from a contrast discrimination experiment used within the model, and demonstrate preliminary results of the model. The IFA is designed to be both physiologically and psychophysically plausible. It consists of a multichannel Gabor pyramid decomposition. The fidelity at each spatial location within each channel is evaluated based on psychometric functions. The psychometric functions were determined experimentally and describe the discrimination ability of the visual system as a function of spatial frequency, orientation, and adaptation level. Limited memory probability summation across the visual channels is used to obtain a measure of perceived image fidelity. Preliminary results of the IFA are consistent with human evaluation of image fidelity.
15389117
A Framework for Automatic Landmark Identification Using a New Method of Nonrigid Correspondence
A framework for automatic landmark identification is presented based on an algorithm for corresponding the boundaries of two shapes. The auto-landmarking framework employs a binary tree of corresponded pairs of shapes to generate landmarks automatically on each of a set of example shapes. The landmarks are used to train statistical shape models, known as point distribution models. The correspondence algorithm locates a matching pair of sparse polygonal approximations, one for each of a pair of boundaries by minimizing a cost function, using a greedy algorithm. The cost function expresses the dissimilarity in both the shape and representation error (with respect to the defining boundary) of the sparse polygons. Results are presented for three classes of shape which exhibit various types of nonrigid deformation.
9776015
Learning to interpret medical images
Statistical shape and appearance models are proving valuable tools for medical image analysis. In this paper we outline the methodology and highlight important recent developments. In particular, we consider an extension to images of differing modality, and describe an optimisation approach to establishing correspondences across a training set of shapes.
3993976
A Software Framework for Creating Patient Specific Geometric Models from Medical Imaging Data for Simulation Based Medical Planning of Vascular Surgery
The primary purpose of vascular surgery is to restore blood flow to organs and tissues. Current methods of vascular treatment planning rely solely on diagnostic and empirical data to guide the decision-making process. This paper details a simulation-based medical planning system for cardiovascular disease that use computational methods to evaluate alternative surgical options prior to treatment using patient-specific models of the vascular system. A software framework, called Geodesic, is mtroduced that reduces the time required to build patient-specific models from medical imaging data from several weeks to less than one day.
16065751
Improving Appearance Model Matching Using Local Image Structure
We show how non-linear representations of local image structure can be used to improve the performance of model matching algorithms in medical image analysis tasks. Rather than represent the image structure using intensity values or gradients, we use measures that indicate the reliability of a set of local image feature detector outputs. These features are image edges, corners, and gradients. Feature detector outputs in flat, noisy regions tend to be ignored whereas those near strong structure are favoured. We demonstrate that combinations of these features give more accurate and reliable matching between models and new images than modelling image intensity alone. We also show that the approach is robust to non-linear changes in contrast, such as those found in multi-modal imaging.