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- W2004113346 abstract "Image algebra is a rigorous, concise notation that unifies linear and nonlinear mathematics in the image domain.Image algebra was developed under DARPA and US Air Force sponsorship at University of Florida for over 15 yearsbeginning in 1984. Image algebra has been implemented in a variety of programming languages designed specifically tosupport the development of image processing and computer vision algorithms and software. The University of Florida hasbeen associated with development of the languages FORTRAN, Ada, Lisp, and C++. The latter implementation involveda class library, iac++, that supported image algebra programming in C++.Since image processing and computer vision are generally performed with operands that are array-based, theMatlab™ programming language is ideal for implementing the common subset of image algebra. Objects include setsand set operations, images and operations on images, as well as templates and image-template convolution operations.This implementation, called Image Algebra Matlab (IAM), has been found to be useful for research in data, image, andvideo compression, as described herein. Due to the widespread acceptance of the Matlab programming language in thecomputing community, IAM offers exciting possibilities for supporting a large group of users. The control over anobject's computational resources provided to the algorithm designer by Matlab means that IAM programs can employversatile representations for the operands and operations of the algebra, which are supported by the underlying librarieswritten in Matlab. In a previous publication, we showed how the functionality of IAC++ could be carried forth into aMatlab implementation, and provided practical details of a prototype implementation called IAM Version 1.In this paper, we further elaborate the purpose and structure of image algebra, then present a maturingimplementation of Image Algebra Matlab called IAM Version 2.3, which extends the previous implementation of IAM toinclude polymorphic operations over different point sets, as well as recursive convolution operations and functionalcomposition. We also show how image algebra and IAM can be employed in image processing and compressionresearch, as well as algorithm development and analysis." @default.
- W2004113346 created "2016-06-24" @default.
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- W2004113346 date "2010-08-19" @default.
- W2004113346 modified "2023-09-23" @default.
- W2004113346 title "Image Algebra Matlab language version 2.3 for image processing and compression research" @default.
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- W2004113346 doi "https://doi.org/10.1117/12.864277" @default.
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