Title

An interpretive programming language for image algebra

Keywords

Image Algebra; Image enhancemen; Image processing

Abstract

Image Algebra (IA) was developed to provide a standard mathematical means of describing image processing algorithms. The goal of IA was to reduce the amount of programming code required in implementing an image processing algorithm. IA has been successful in expressing many linear and nonlinear image processing algorithms in a short and concise manner using a basic set of operators. When placed in a programming environment, IA enables the programmer to write image processing algorithms at a high level of abstraction and with a high degree of readability. IA functions have been developed for several programming languages such as ADA, FORTRAN, and C either as an external library or as a preprocessor. The IA programming implementation presented (Basic Image Algebra Interpreter: BlAT) here was designed and built around the direct implementation of the IA operators providing a means of adding functions directly related to IA to the programming language. For example, image and template data types were added to the language allowing for the manipulation of images without the concern of defining the data structure prior to its use. Several of the key issues in designing the programming language will be presented, along with several image processing algorithm examples comparing a standard C language implementation to the Basic Image Algebra Interpreted language implementation.

Publication Date

6-30-1994

Publication Title

Proceedings of SPIE - The International Society for Optical Engineering

Volume

2300

Number of Pages

180-191

Document Type

Article; Proceedings Paper

Identifier

scopus

Personal Identifier

scopus

DOI Link

https://doi.org/10.1117/12.179189

Socpus ID

85076807746 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85076807746

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