Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multi-hop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show the LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional outing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.

/pdf/energy-efficient-communication-protocol-for-wireless-4vhuagusz2.pdf

Energy-efficient communication protocol for wireless microsensor networks

Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have signicant impact on the overall energy dissipation of these networks. Based on our ndings that the conventional protocols of direct transmission, minimum-transmission-energy, multihop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster base stations (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show that LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional routing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.

Energy-efficient communication protocols for wireless microsensor networks

Determining optical flow

Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

An automated method for segmenting magnetic resonance head images into brain and non-brain has been developed. It is very robust and accurate and has been tested on thousands of data sets from a wide variety of scanners and taken with a wide variety of MR sequences. The method, Brain Extraction Tool (BET), uses a deformable model that evolves to fit the brain's surface by the application of a set of locally adaptive model forces. The method is very fast and requires no preregistration or other pre-processing before being applied. We describe the new method and give examples of results and the results of extensive quantitative testing against "gold-standard" hand segmentations, and two other popular automated methods.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/hbm.10062

Fast robust automated brain extraction

Historically, multiple description coding (MDC) and postprocessing error concealment (ECN) algorithms have evolved separately. In this paper, we propose a coordinated application of multiple description scalar quantizers (MDSQ) and ECN, where the smoothness of the video signal helps to compensate for the loss of descriptions. In particular, we perform a reconstruction that is consistent with the data received at the decoder. When only a single description is available, the video is reconstructed in such a way that: 1) if we were to regenerate two descriptions (from the reconstructed video), one of them would be equivalent to the received description and 2) the reconstructed video is spatiotemporally smooth. Experimental results with several video sequences demonstrated a peak signal-to-noise ratio (PSNR) improvement of 0.9-2.8 dB for intracoded frames. The PSNR improvements for intercoded frames were negligible. However, for both cases, the visual improvements were much more striking than what the PSNR improvement suggested.

Coordinated application of multiple description scalar quantization and error concealment for error-resilient MPEG video streaming

An imaging system produces a degraded measurement of a real-valued quantity that varies temporally, spectrally, and spatially. When there are multiple measurements of the same scene, it is possible to combine the nonredundant information in those measurements and produce an improved image that has more information than any of the measurements does alone. This type of reconstruction is known as image fusion. Depending on the diversity of information in the measurements, it is possible to achieve temporal, spectral, spatial, and gray-scale improvements with an image fusion algorithm. In this paper, we are proposing an image fusion algorithm that produces an image of higher spatial and gray-scale information from multiple measurements. The algorithm estimates the spatial and illumination correlation between multiple measurements, and employs a set-theoretic reconstruction technique.

Multiframe information fusion for gray-scale and spatial enhancement of images

An efficient algorithm for the determination of the coefficients of a polynomial from evenly spaced sample values of that polynomial on a spiral contour in the complex plane is presented. It is useful for the determination of a sequence from evenly spaced values of its Fourier transform.

An algorithm for performing an inverse chirp z-transform

This paper is concerned with the use of 2-D linear prediction for image segmentation. It begins with a brief summary of the mathematics involved in 2-D linear predictive analysis of arbitrarily-shaped regions. Then, it introduces a 2-D LPC distance measure based on the error residual of 2-D linear prediction. Finally, it describes how the above results can be applied to image segmentation using a simple cluster seeking algorithm. The results indicate that arbitrarily-shaped image regions can be well identified and clustered using as features their 2-D LPC parameters.

Two-dimensional linear predictive analysis of arbitrarily-shaped regions

In this paper we discuss an end-to-end system for SAR automatic target recognition (ATR), giving particular emphasis to the discrimination and classification stages. The ATR system employs a three sequential stage approach to reduce complexity: a detection stage, a discrimination stage, and a classification stage. Details of the detection stage were presented previously. The target discrimination and classification methods, which we present here, involve extracting rotationally and translationally invariant features from the Radon transform of target chips. The methods are applied in both isolated and complete end-to-end systems on the TESAR baseline SAR database distributed by the U.S. Army Research Laboratory and in isolation using the public MSTAR database. The performance results on these SAR datasets are presented.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Russell M. Mersereau

Papers

Coordinated application of multiple description scalar quantization and error concealment for error-resilient MPEG video streaming

Multiframe information fusion for gray-scale and spatial enhancement of images

An algorithm for performing an inverse chirp z-transform

Two-dimensional linear predictive analysis of arbitrarily-shaped regions

Efficient end-to-end feature-based system for SAR ATR