Boost的成员Generic Image Library图像库

来源：互联网发布：巴恩斯第七场数据编辑：程序博客网时间：2024/05/18 18:18

原帖http://ihome.ust.hk/~fuhb/cgi-bin/index.php?entry=entry061114-141001

如果你没有一个用的称手的图像库，你可能会在CImg，Devil，FreeImage等图像库之间徘徊，不知道哪个库更加适合自己。最近由Adobe开发的Generic Image Library （简称GIL）刚刚通过boost的认证，被boost接受成为其一部分。这个对于经常使用stl的编程人员来说无疑是一个好消息。下面是GIL的设计目标：
* Generality: Abstracts image representations from algorithms on images. It allows for writing code once and have it work for any image type.
* Performance: Speed has been instrumental to the design of the library. The generic algorithms provided in the library are comparable in speed to hand-coding the algorithm for a specific image type.
* Flexibility: Compile-type parameter resolution results in faster code, but severely limits code flexibility. The library allows for any image parameter to be specified at run time (for a minor performance cost comparable to a virtual call overhead).
* Extensibility: GIL is concept-based and allows virtually every component - channels, color spaces, pixels, pixel iterators, locators, views, images and algorithms - to be replaced.
* Compatibility: The library is designed as an STL and Boost complement. Generic STL algorithms can be used for pixel manipulation, and they are especially optimized. The library works natively on existing raw pixel data.

在Adobe Open Source的官方网站有对GIL的详细介绍（http://opensource.adobe.com/gil），包括Source code，Tutorial，Design Guide，还有一个55的视频介绍。