"This book gives readers an intuitive appreciation for randomfunctions, plus theory and processes necessary for sophisticatedapplications. It covers probability theory, random processes,canonical representation, optimal filtering, and random models.Second in the SPIE/IEEE Series on Imaging Science &Engineering.It also presents theory along with applications, to help readersintuitively appreciate random functions.Included are special cases in which probabilistic insight is morereadily achievable. When provided, proofs are in the main body ofthe text and clearly delineated; sometimes they are either notprovided or outlines of conceptual arguments are given. The intentis to state theorems carefully and to draw clear distinctionsbetween rigorous mathematical arguments and heuristic explanations.When a proof can be given at a mathematical level commensurate withthe text and when it enhances conceptual understanding, it isusually provided; in other cases, the effort is to explainsubtleties of the definitions and properties concerning randomfunctions, and to state conditions under which a propositionapplies. Attention is drawn to the differences betweendeterministic concepts and their random counterparts, for instance,in the mean-square calculus, orthonormal representation, and linearfiltering. Such differences are sometimes glossed over in methodbooks; however, lack of differentiation between random anddeterministic analysis can lead to misinterpretation ofexperimental results and misuse of techniques.The author's motivation for the book comes from his experience inteaching graduate-level image processing and having to end upteaching random processes. Even students who have taken a course onrandom processes have often done so in the context of linearoperators on signals. This approach is inadequate for imageprocessing. Nonlinear operators play a widening role in imageprocessing, and the spatial nature of imaging makes itsignificantly different from one-dimensional signal processing.Moreover, students who have some background in stochastic processesoften lack a unified view in terms of canonical representation andorthogonal projections in inner product spaces."

Edward R. Dougherty is director of the Imaging Division of theTexas Center for Applied Technology and professor of g at Texas A&M University

Second in the SPIE/IEEE Series on Imaging Science &Engineering. It also presents theory along with applications, to help readersintuitively appreciate random functions. Included are special cases in which probabilistic insight is morereadily achievable. Edward R. Dougherty is director of the Imaging Division of theTexas Center for Applied Technology and professor of g at Texas A&M University. He holds an MS in computerscience from Stevens Institute of Technology and a PhD inmathematics from Rutgers University.

Start by marking Random Processes for Image Signal Processing as Want to Read . This book gives readers an intuitive appreciation for random functions, plus theory and processes necessary for sophisticated applications.

Start by marking Random Processes for Image Signal Processing as Want to Read: Want to Read savin. ant to Read. Second in the SPIE/IEEE Series on Imaging Science & Engineering. It also presents theory along with applications, to he This book gives readers an intuitive appreciation for random functions, plus theory and processes necessary for sophisticated applications.

Author(s): Edward R. Dougherty. This book provides a framework for understanding the ensemble of temporal, spatial, and higher-dimensional processes in science and engineering that vary randomly in observations

Author(s): Edward R. This book provides a framework for understanding the ensemble of temporal, spatial, and higher-dimensional processes in science and engineering that vary randomly in observations. Suitable as a text for undergraduate and graduate students with a strong background in probability and as a graduate text in image processing courses. Table of contents show all chapter outlines +. Save this book to your library. This will count as one of your downloads.

This book gives readers an intuitive appreciation for random functions, plus theory and processes necessary for sophisticated applications. It also presents theory along with applications, to help readers intuitively appreciate random functions. Included are special cases in which probabilistic insight is more readily achievable.

Home . Details for: Random processes for image and signal . Details for: Random processes for image and signal processing /. Normal view MARC view ISBD view. Random processes for image and signal processing, Edward R. By: Dougherty, Edward R. Material type: BookSeries: SPI/IEEE series on imaging science & engineering.

Random Processes for Image and Signal Processing Edward . ougherty Second in the SPIE/IEEE Series on Imaging Science &Engineering Science and engineering deal with temporal, spatial,and higher-dimensional processes that vary randomly fromobservation to observation. Deterministic analysis does not providea framework for understanding the ensemble of observations, nordoes it provide a mechanism for predicting future events. Randomprocesses provide the tools to bridge these gaps

Dougherty is the author of 16 books ranging from basic probability books to advanced computational biology and genomic systems . Dougherty, Edward (1999). Random Processes for Image and Signal Processing

Dougherty is the author of 16 books ranging from basic probability books to advanced computational biology and genomic systems engineering ones. He proposed the Probabilistic Boolean Network (PBN) model for gene regulatory networks. PBNs have been extensively used for intervention and classification in genomic problems . Random Processes for Image and Signal Processing. Bellingham: Series on Imaging Science and Engineering, SPIE Press and IEEE Presses.

It covers probability theory, random processes, canonical representation .

Second in the SPIE/IEEE Series on Imaging Science Engineering. Dougherty is director of the Imaging Division of the Texas Center for Applied Technology and professor of Electrical Engineering at Texas A&M University.

Random processes provide the tools to bridge these gaps. Readers of this book will gain an intuitive appreciation of random functions, in addition to understanding theory and processes necessary for sophisticated applications. The initial chapter covers basic theory of probability, with special attention to multivariate distributions and functions of several random variables.

Goutsias J (1992) Morphological analysis of discrete random shapes.

IEEE, New York, pp 121–162Google Scholar. Giardina R, Dougherty ER (1988) Morphological methods in image and signal processing. Prentice-Hall, Englewood Cliffs, p 82Google Scholar. Goutsias J (1992) Morphological analysis of discrete random shapes. J Math Imaging Vis 2(2/3):193–rossRefGoogle Scholar. Haralick RM, Sternberg SR, Zhuang X (1987) Image analysis using mathematical morphology.