Springer us dez 1990 (2 Ergebnisse)

Buch. Zustand: Neu. Neuware - This monograph evolved from my Ph. D dissertation completed at the Laboratory of Computer Science, MIT, during the Summer of 1986. In my dissertation I proposed a pipelined code mapping scheme for array operations on static dataflow architectures. The main addition to this work is found in Chapter 12, reflecting new research results developed during the last three years since I joined McGill University-results based upon the principles in my dissertation. The terminology dataflow soft ware pipelining has been consistently used since publication of our 1988 paper on the argument-fetching dataflow architecture model at McGill University [43]. In the first part of this book we describe the static data flow graph model as an operational model for concurrent computation. We look at timing considerations for program graph execution on an ideal static dataflow computer, examine the notion of pipe lining, and characterize its performance. We discuss balancing techniques used to transform certain graphs into fully pipelined data flow graphs. In particular, we show how optimal balancing of an acyclic data flow graph can be formulated as a linear programming problem for which an optimal solution exists. As a major result, we show the optimal balancing problem of acyclic data flow graphs is reduceable to a class of linear programming problem, the net work flow problem, for which well-known efficient algorithms exist. This result disproves the conjecture that such problems are computationally hard.…

Buch. Zustand: Neu. Neuware - One of the most intriguing questions in image processing is the problem of recovering the desired or perfect image from a degraded version. In many instances one has the feeling that the degradations in the image are such that relevant information is close to being recognizable, if only the image could be sharpened just a little. This monograph discusses the two essential steps by which this can be achieved, namely the topics of image identification and restoration. More specifically the goal of image identifi cation is to estimate the properties of the imperfect imaging system (blur) from the observed degraded image, together with some (statistical) char acteristics of the noise and the original (uncorrupted) image. On the basis of these properties the image restoration process computes an estimate of the original image. Although there are many textbooks addressing the image identification and restoration problem in a general image processing setting, there are hardly any texts which give an indepth treatment of the state-of-the-art in this field. This monograph discusses iterative procedures for identifying and restoring images which have been degraded by a linear spatially invari ant blur and additive white observation noise. As opposed to non-iterative methods, iterative schemes are able to solve the image restoration problem when formulated as a constrained and spatially variant optimization prob In this way restoration results can be obtained which outperform the lem. results of conventional restoration filters.…