Image Processing for Remote Sensing

Edited by leaders in the field, with contributions by a panel of experts, Image Processing for Remote Sensing explores new and unconventional mathematics methods. The coverage includes the physics and mathematical algorithms of SAR images, a comprehensive treatment of MRF-based remote sensing image classification, statistical approaches for improved classification with the remote sensing data, Wiener filter-based method, and other modern approaches and methods of image processing for remotely sensed data. Each chapter explores a technique for dealing with a specific remote sensing problem. The book offers physical insights on the steps for constructing various digital seismic images. The volume examines image modeling, statistical image classifiers, change detection, independent component analysis, vertex component analysis, image fusion for better classification. It explores unique topics such as accuracy assessment and information-theoretic measure of multiband images and many chapters emphasize issues with synthetic aperture radar (SAR) images. Continued development on imaging sensors creates new opportunities and challenges in image processing for remote sensing. Image Processing for Remote Sensing not only presents the most up to date developments of image processing for remote sensing but also suggests to readers the many challenging problems ahead for further study.

The use of simulation modeling and analysis is becoming increasingly more popular as a technique for improving or investigating process performance. This book is a practical, easy-to-follow reference that offers up-to-date information and step-by-step procedures for conducting simulation studies. It provides sample simulation project support material, including checklists, data-collection forms, and sample simulation project reports and publications to facilitate practitioners' efforts in conducting simulation modeling and analysis projects.

Simulation Modeling Handbook: A Practical Approach has two major advantages over other treatments. First, it is independent of any particular simulation software, allowing readers to use any commercial package or programming language. Second, it was written to insulate practitioners from unnecessary simulation theory that does not focus on their average, practical needs.

As the popularity of simulation studies continues to grow, the planning and execution of these projects, more and more engineering and management professionals will be called upon to perform these tasks. With its simple, no-nonsense approach and focus on application rather than theory, this comprehensive and easy-to-understand guide is the ideal vehicle for acquiring the background and skills needed to undertake effective simulation projects.

Features

• Presents step-by-step procedures for conducting successful simulation modeling and analysis
  
• Addresses every phase of performing simulations, from formulating the problem to presenting study results and recommendations
  
• Uses approaches applicable regardless of the specific simulation or software used
  
• Includes a summary of the major simulation software packages and discusses the pros and cons of using general purpose programming languages

Simulation modeling is becoming increasingly popular as a technique for evaluating the performance of resource allocation and alternate operating policies. This handbook is a practical, easy-to-follow reference that offers step-by-step procedures for conducting simulation studies that help decision-makers find the optimal courses of action. The objective of this chapter is to provide the simulation practitioner with some basic information about simulation modeling and analysis.