opencv学习笔记（八）-IplImage数据结构

IplImage介绍

typedef struct _IplImage
{int  nSize;             /* sizeof(IplImage) */int  ID;                /* version (=0)*/int  nChannels;         /* Most of OpenCV functions support 1,2,3 or 4 channels */int  alphaChannel;      /* Ignored by OpenCV */int  depth;             /* Pixel depth in bits: IPL_DEPTH_8U, IPL_DEPTH_8S, IPL_DEPTH_16S,IPL_DEPTH_32S, IPL_DEPTH_32F and IPL_DEPTH_64F are supported.  */char colorModel[4];     /* Ignored by OpenCV */char channelSeq[4];     /* ditto */int  dataOrder;         /* 0 - interleaved color channels, 1 - separate color channels.cvCreateImage can only create interleaved images */int  origin;            /* 0 - top-left origin,1 - bottom-left origin (Windows bitmaps style).  */int  align;             /* Alignment of image rows (4 or 8).OpenCV ignores it and uses widthStep instead.    */int  width;             /* Image width in pixels.                           */int  height;            /* Image height in pixels.                          */struct _IplROI *roi;    /* Image ROI. If NULL, the whole image is selected. */struct _IplImage *maskROI;      /* Must be NULL. */void  *imageId;                 /* "           " */struct _IplTileInfo *tileInfo;  /* "           " */int  imageSize;         /* Image data size in bytes(==image->height*image->widthStepin case of interleaved data)*/char *imageData;        /* Pointer to aligned image data.         */int  widthStep;         /* Size of aligned image row in bytes.    */int  BorderMode[4];     /* Ignored by OpenCV.                     */int  BorderConst[4];    /* Ditto.                                 */char *imageDataOrigin;  /* Pointer to very origin of image data(not necessarily aligned) -needed for correct deallocation */
}
IplImage;

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depth变量：像素的深度。深度值有：

#define IPL_DEPTH_1U     1
#define IPL_DEPTH_8U     8
#define IPL_DEPTH_16U   16
#define IPL_DEPTH_32F   32#define IPL_DEPTH_8S  (IPL_DEPTH_SIGN| 8)
#define IPL_DEPTH_16S (IPL_DEPTH_SIGN|16)
#define IPL_DEPTH_32S (IPL_DEPTH_SIGN|32)

通俗一点讲就是像素的取值大小，例如：IPL_DEPTH_8U 即代表有8位数据，最大值256，即一个像素的颜色等级分为256种。从0到256不断加深。

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nChannels变量：图像通道（通道的概念之前有介绍）。
彩色图像的排列方式：
彩色图像一般是由3通道表示。3通道表示一个像素点有三个值，分别对应R,G,B.RGB决定该像素点的颜色。

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一下其他的重要参数：
imageData 包含一个指向第一行图像数据的指针。
widthStep是指一个排列图像行的大小，以字节为单位。
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访问图像数据

实例：分别打印一个彩色图像和R,G,B三个单通道的图像

int main()
{IplImage* img;img = cvLoadImage("F:\\Opencv\\素材\\楪析.jpg");IplImage* b_img = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);IplImage* g_img = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);IplImage* r_img = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);int x, y;for (y = 0; y < img->height; y++){unsigned char* prow = (unsigned char*)(img->imageData + y*img->widthStep);unsigned char* brow = (unsigned char*)(b_img->imageData + y*b_img->widthStep);unsigned char* grow = (unsigned char*)(g_img->imageData + y*g_img->widthStep);unsigned char* rrow = (unsigned char*)(r_img->imageData + y*r_img->widthStep);for (x = 0; x < img->width; x++){brow[x] = prow[3 * x + 0];grow[x] = prow[3 * x + 1];rrow[x] = prow[3 * x + 2];}}cvNamedWindow("1");cvShowImage("1", img);cvNamedWindow("b");cvShowImage("b", b_img);cvNamedWindow("r");cvShowImage("r", r_img);cvNamedWindow("g");cvShowImage("g", g_img);cvWaitKey(0);return 0;}

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对ROI和widthStep的补充

ROI全称：region of interest,即：感兴趣的区域。使用ROI可以对图像的部分区域进行操作而不是对图像额整个区域进行运算，可以提高计算机视觉代码的执行速度。
例：用imageROI来增加某范围的像素。

int main()
{IplImage* img;img = cvLoadImage("F:\\Opencv\\素材\\楪析.jpg");CvRect rect;rect.x = 350;rect.y = 102;rect.width = 166;rect.height = 141;cvSetImageROI(img, rect);cvAddS(img, cvScalar(150), img);cvResetImageROI(img);cvNamedWindow("1");cvShowImage("1", img);cvWaitKey(0);return 0;
}

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介绍几个主要函数：
cvSetImageROI()和cvResetImageROI()这两个函数用来设置和取消ROI，
void cvSetImageROI(IplImage* image,CvRect rect);
需要传递一个图像指针和矩阵，这个矩阵

typedef struct CvRect
{int x;int y;int width;int height;
}
CvRect;

x,y是ROI图像起始点的坐标，width和height是ROI图像的宽度和高度。
图像指针是指我们选取ROI区域的母图像。

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我们可以使用widthStep达到同样的效果，
首先我们要创建一个CvRect结构体,设置图像起点和大小。
然后创建一个图像头，让它的width和height和之前创建CvRect结构体的width和height相同，并且让它的通道和像素深度与母图像的相同。
在使图像头的origin（起点）和widthStep（步长）和母图像相同，
可以理解为创建一个大小与母图像相等CvRect结构体指定的图像区域有颜色，其他地方是透明的图像覆盖在母图像上面。例程如下：

int main()
{IplImage* interest_img = cvLoadImage("F:\\Opencv\\素材\\楪析.jpg");CvRect interest_rect = cvRect(350, 102, 166, 141);IplImage* sub_img = cvCreateImageHeader(cvSize(interest_rect.width, interest_rect.height),interest_img->depth,interest_img->nChannels);sub_img->origin = interest_img->origin;sub_img->widthStep = interest_img->widthStep;sub_img->imageData = interest_img->imageData + interest_img->widthStep*interest_rect.y +interest_img->nChannels*interest_rect.x;cvAddS(sub_img, cvScalar(150), sub_img);cvNamedWindow("interest_img");cvNamedWindow("sub_img");cvShowImage("interest_img", interest_img);cvShowImage("sub_img", sub_img);cvResetImageROI(sub_img);cvWaitKey(0);cvDestroyWindow("interest_img");cvDestroyWindow("sub_img");interest_img = NULL;sub_img = NULL;return 0;
}

看起来设置和重置ROI更方便一些，为什么还要使用widthStep？原因在于有些时候在处理的过程中，想在操作过程中设置和保持一幅图像的多个子区域处于活动状态，但是ROI只能串行处理并且必须不断地设置和重置。