陷入虚无的天狼

计算机图像类库
1.IPL ( Intel Image Processing Library) Intel公司出品，收费。

2.OpenCV

http://sourceforge.net/projects/opencvlibrary/
http://www.opencv.org.cn/index.php/首页
开放源代码的计算机视觉类库OpenCv ( Intel Open SourceComputerVision L ibrary)由英特尔公司位于俄罗斯的研究实验室所开发,它是一套可免费获得的由一些C函数和C ++类所组成的库,用来实现一些常用的图像处理及计算机视觉算法。OpenCv与英特尔公司所开发的另一图像处理库IPL ( Intel Image Processing L ibrary)兼容, IPL(收费)用于实现对数字图像的一些低级处理,而OpenCv则主要用于对图像进行一些高级处理,比如说特征检测与跟踪、运动分析、目标分割与识别以及3D 重建等。由于OpenCv的源代码是完全开放的,而且源代码的编写简洁而又高效,特别是其中大部分的函数都已经过汇编最优化,以使之能高效而充分地利用英特尔系列处理芯片的设计体系,对于PentiumMMX, Pentium, PentiumⅢ及Pentium4这些处理器而言,OpenCv的代码执行效率是非常高的,所以近年来在国外的图像处理相关领域中被广泛地使用,成为一种流行的图像处理软件。

3.FreeImage

http://freeimage.sourceforge.net/

C语言的体系，大量使用指针运算速度可以保证，内含先进的多种插值算法。另外独有的支持meta exif信息的读取。该库最大的特点就是比较简练，只把重点放在对各种格式图像的读取写入支持上，没有显示部分，实际编程的时候还是需要调用API函数进行显示

4. Adobe GIL(Generic Image Library)

http://opensource.adobe.com/gil/

通过boost的认证，被boost接受成为其一部分。

5.DevIL

http://openil.sourceforge.net/

6.CxImage

http://www.codeproject.com/bitmap/cximage.asp

该开发包完全开放源代码，图像封装为一个类，功能极为强大，与Windows、MFC支持极好，支持图像的多种操作（线性滤波、中值滤波、直方图操作、旋转缩放、区域选取、阈值处理、膨胀腐蚀、alpha混合等等），支持从文件、内存或者win32api定义的位图图像格式中读取图像，支持将图像显示在任意窗口，功能可谓很强大了，而且对像素的操作很方便，另外还有一个界面很强的demo，可以直接在上面进行二次开发，推荐使用！
缺点：里面的子库很多，用起来可能较麻烦；而且感觉速度稍慢

7.CImg

就一个.h文件所以用起来很简明，但感觉功能上不如CxImage。可以与CxImage配合使用，因为CImg提供了基于lapack的矩阵运算函数和完善的线性滤波卷积函数，同时CImg做像素运算还是很方便的。另外，独有Display类可以方便的实现各种显示，包括显示图像、打字、画线等等。还有，该库有个基于光流的多尺度图像配准例子，很好

Matt wrote:
> Does the language have header files containing definitions of numbers
> such as pi and e?
>
> I believe some implementations used to have those, but I can't find them
> in Stroustrup.
>
> Thanks.

FWIW...

There is a history to trying to solve constants problem in an elegant
way with various solutions having being proposed and rejected on
gmane.comp.lib.boost.devel newsgroup.

The solutions fell into 4 areas IIRC:

solution1: Use a variable e.g

//some math header

extern const double pi;

Note that one shouldnt define it in the header due to the ODR rule so
it would require linking a library in the application or defining in a
source file, which was felt to be inconvenient. The other drawback was
that it cant simultaneously be float, double and long double so it will
never be right for everybody.

solution 2: use a function e.g

inline double pi()
{
return  3.141592653589793238462643383279502884197;
}

This suffers in that you cant control the floating point type and it
seems that people hate the function notation to call it. You could make
it a template of course, but you would have to provide the template
parameter when invoked.

solution 3: Use a smart object

struct pi{
template <typename T>
T pi_function(); // get pi as a T
template <typename T>
operator T()  { return pi_function<T>();}
}

This may or may not be how it went. Whatever... The problem this had
was deducing the type to convert to in some situations IIRC.

solution 4: My preferred solution and the one I use, but suffers from
various of the problems above

template <typename T>
struct constant_{

static const T pi;
static const T e;
};

// convenient version for My Favourite float
#ifndef MY_FAVOURITE_FLOAT
#define MY_FAVOURITE_FLOAT double
#endif
struct constant : constant_<MY_FAVOURITE_FLOAT>{};

int main()
{
float val1 = constant_<float>::pi;
double val = constant::pi;
}

Of course this requires a library or source and visible use of
templates in the first invocation at least.


Finally there is an M_PI macro available in some versions of <cmath>
normally via its nested include <math.h>, but that is horrible...

So If anyone has any ideas .... ???

regards
Andy Little