A sorter-based architecture for a parallel implementation of communication intensive algorithms

This paper deals with the parallel execution of algorithms with global and/or irregular data dependencies on a regularly and locally connected processor array. The associated communication problems are solved by the use of a two-dimensional sorting algorithm. The proposed architecture, which is based on a two-dimensional sorting network, offers a high degree of flexibility and allows an efficient mapping of many irregularly structured algorithms. In this architecture a one-dimensional processor array performs all required control and arithmetic operations, whereas the sorter solves complex data transfer problems. The storage capability of the sorting network is also used as memory for data elements. The algorithms for sparse matrix computations, fast Fourier transformation and for the convex hull problem, which are mapped onto this architecture, as well as the simulation of a shared-memory computer show that the utilization of the most complex components, the processors, is O(1).     

An empirical InSAR-optical fusion approach to mapping vegetation canopy height

Exploiting synergies afforded by a host of recently available national-scale data sets derived from interferometric synthetic aperture radar (InSAR) and passive optical remote sensing, this paper describes the development of a novel empirical approach for the provision of regional- to continental-scale estimates of vegetation canopy height. Supported by data from the 2000 Shuttle Radar Topography Mission (SRTM), the National Elevation Dataset (NED), the LANDFIRE project, and the National Land Cover Database (NLCD) 2001, this paper describes a data fusion and modeling strategy for developing the first-ever high-resolution map of canopy height for the conterminous U.S. The approach was tested as part of a prototype study spanning some 62,000 km² in central Utah (NLCD mapping zone 16). A mapping strategy based on object-oriented image analysis and tree-based regression techniques is employed. Empirical model development is driven by a database of height metrics obtained from an extensive field plot network administered by the USDA Forest Service-Forest Inventory and Analysis (FIA) program. Based on data from 508 FIA field plots, an average absolute height error of 2.1 m (r = 0.88) was achieved for the prototype mapping zone.     

Estimation in Random Coefficient Autoregressive Models

Abstract. We propose the quasi‐maximum likelihood method to estimate the parameters of an RCA(1) process, i.e. a random coefficient autoregressive time series of order 1. The strong consistency and the asymptotic normality of the estimators are derived under optimal conditions.     

Photocurrents and degradation rates on particulate TiO2 layers: Effect of layer thickness, concentration of oxidizable substance and illumination direction

Different routes for immobilization of TiO₂ on conducting substrates were compared to find active and stable photocatalysts, which could either be operated in open circuit (photocatalysis) or with applied electric potential (photoelectrocatalysis). The advantage of applying an electric potential was investigated. Polarization curves and photoelectrochemical degradation reactions served to characterize catalysts and to find a way of predicting the optimum synthesis conditions. The difference between front side (EE) and back side (SE) illumination is discussed as a function of layer thickness, as well as the influence of oxidizable substance concentration on photocurrents. Stability of catalysts was investigated in repetitive degradation experiments.     

Deblurring Shaken and Partially Saturated Images

We address the problem of deblurring images degraded by camera shake blur and saturated (over-exposed) pixels. Saturated pixels violate the common assumption that the image-formation process is linear, and often cause ringing in deblurred outputs. We provide an analysis of ringing in general, and show that in order to prevent ringing, it is insufficient to simply discard saturated pixels. We show that even when saturated pixels are removed, ringing is caused by attempting to estimate the values of latent pixels that are brighter than the sensor’s maximum output. Estimating these latent pixels is likely to cause large errors, and these errors propagate across the rest of the image in the form of ringing. We propose a new deblurring algorithm that locates these error-prone bright pixels in the latent sharp image, and by decoupling them from the remainder of the latent image, greatly reduces ringing. In addition, we propose an approximate forward model for saturated images, which allows us to estimate these error-prone pixels separately without causing artefacts. Results are shown for non-blind deblurring of real photographs containing saturated regions, demonstrating improved deblurred image quality compared to previous work.