Java Advanced Imaging API: A Tutorial
This tutorial shows how the Java language and its Java Advanced Imaging (JAI) Application Program Interface (API) can be used to create applications for image representation, processing and visualization. The Java language advantages are its low cost, licensing independence and inter-platform portability. The JAI API advantages are its flexibility and variety of image processing operators. The purpose of this tutorial is to present the basic concepts of the JAI API, including several complete an verified code samples which implements simple image processing and visualization operations. At the end of the tutorial the reader should be able to implement his/her own algorithms using the Java language and the JAI API.
In spite of the existence of several image processing softwares with many image processing functions, tailored for several different uses, there is often the need for implementation of specific algorithms which are not available on those softwares – for example, a user may want to implement his/her own image classification or filtering algorithm or tweak some already implemented algorithm parameters. Some of those softwares allow the development of user-defined modules, often using the same API developed for the software itself. The developer may be able to use those APIs to develop his/hew own routines, but often there is an additional cost or licensing restrictions.
A royalty-free, portable, flexible alternative for the implementation of generic applications is the Java language [1]. For image processing and representation, the JAI (Java Advanced Imaging) API (Application Program Interface) [2] can be used. Although the API is not part of a full-featured image processing software, the existing functions and extension possibilities allied to the low cost and ease of implementation makes this combination an attractive option for image processing algorithms development.
This tutorial will present some concepts on the JAI API and give code samples and short code snippets for image input and output, application of basic operators, image visualization and image data manipulation. The tutorial will not present some details like installation and configuration issues or advanced operations such as network imaging. It is assumed that the reader already have a good knowledge of Java or other modern languages (C++, Delphi) and basic image processing knowledge.
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Tags: algorithm parameters, apis, application program interface, attractive option, code samples, existence, extension possibilities, flexibility, generic applications, image classification, image processing algorithms, image processing software, image representation, jai, java advanced imaging, java language, platform portability, royalty, spite, visualization
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