对图片进行操作时经常会涉及到不同通道数据提取，在OpenCV中提供了很多比较便捷的操作函数，本文涉及函数如下：
1.cvtColor 颜色空间转换
2.convertTo 图片数据类型转换
3.split 图片通道分离
4.merge 图片不同通道合并
5.extractChannel 抽取图片某一个通道
6.applyColorMap 灰度图转伪彩色图
1.函数cvtColor
定义：
void cvtColor( InputArray src, OutputArray dst, int code, int dstCn = 0 );
def cvtColor(src, code, dst=None, dstCn=None)
作用:图像颜色转换。
参数：
src：输入图像
dst：输出图像
dstCn:转换后目标图像通道，通常采用默认值
code:转换类型，可以取下列枚举值
enum ColorConversionCodes {
COLOR_BGR2BGRA = 0,
COLOR_RGB2RGBA = COLOR_BGR2BGRA,
COLOR_BGRA2BGR = 1,
COLOR_RGBA2RGB = COLOR_BGRA2BGR,
COLOR_BGR2RGBA = 2,
COLOR_RGB2BGRA = COLOR_BGR2RGBA,
COLOR_RGBA2BGR = 3,
COLOR_BGRA2RGB = COLOR_RGBA2BGR,
COLOR_BGR2RGB = 4,
COLOR_RGB2BGR = COLOR_BGR2RGB,
COLOR_BGRA2RGBA = 5,
COLOR_RGBA2BGRA = COLOR_BGRA2RGBA,
COLOR_BGR2GRAY = 6,
COLOR_RGB2GRAY = 7,
COLOR_GRAY2BGR = 8,
COLOR_GRAY2RGB = COLOR_GRAY2BGR,
COLOR_GRAY2BGRA = 9,
COLOR_GRAY2RGBA = COLOR_GRAY2BGRA,
COLOR_BGRA2GRAY = 10,
COLOR_RGBA2GRAY = 11,
COLOR_BGR2BGR565 = 12,
COLOR_RGB2BGR565 = 13,
COLOR_BGR5652BGR = 14,
COLOR_BGR5652RGB = 15,
COLOR_BGRA2BGR565 = 16,
COLOR_RGBA2BGR565 = 17,
COLOR_BGR5652BGRA = 18,
COLOR_BGR5652RGBA = 19,
COLOR_GRAY2BGR565 = 20,
COLOR_BGR5652GRAY = 21,
COLOR_BGR2BGR555 = 22,
COLOR_RGB2BGR555 = 23,
COLOR_BGR5552BGR = 24,
COLOR_BGR5552RGB = 25,
COLOR_BGRA2BGR555 = 26,
COLOR_RGBA2BGR555 = 27,
COLOR_BGR5552BGRA = 28,
COLOR_BGR5552RGBA = 29,
COLOR_GRAY2BGR555 = 30,
COLOR_BGR5552GRAY = 31,
COLOR_BGR2XYZ = 32,
COLOR_RGB2XYZ = 33,
COLOR_XYZ2BGR = 34,
COLOR_XYZ2RGB = 35,
COLOR_BGR2YCrCb = 36,
COLOR_RGB2YCrCb = 37,
COLOR_YCrCb2BGR = 38,
COLOR_YCrCb2RGB = 39,
COLOR_BGR2HSV = 40,
COLOR_RGB2HSV = 41,
COLOR_BGR2Lab = 44,
COLOR_RGB2Lab = 45,
COLOR_BGR2Luv = 50,
COLOR_RGB2Luv = 51,
COLOR_BGR2HLS = 52,
COLOR_RGB2HLS = 53,
COLOR_HSV2BGR = 54,
COLOR_HSV2RGB = 55,
COLOR_Lab2BGR = 56,
COLOR_Lab2RGB = 57,
COLOR_Luv2BGR = 58,
COLOR_Luv2RGB = 59,
COLOR_HLS2BGR = 60,
COLOR_HLS2RGB = 61,
COLOR_BGR2HSV_FULL = 66,
COLOR_RGB2HSV_FULL = 67,
COLOR_BGR2HLS_FULL = 68,
COLOR_RGB2HLS_FULL = 69,
COLOR_HSV2BGR_FULL = 70,
COLOR_HSV2RGB_FULL = 71,
COLOR_HLS2BGR_FULL = 72,
COLOR_HLS2RGB_FULL = 73,
COLOR_LBGR2Lab = 74,
COLOR_LRGB2Lab = 75,
COLOR_LBGR2Luv = 76,
COLOR_LRGB2Luv = 77,
COLOR_Lab2LBGR = 78,
COLOR_Lab2LRGB = 79,
COLOR_Luv2LBGR = 80,
COLOR_Luv2LRGB = 81,
COLOR_BGR2YUV = 82,
COLOR_RGB2YUV = 83,
COLOR_YUV2BGR = 84,
COLOR_YUV2RGB = 85,
COLOR_YUV2RGB_NV12 = 90,
COLOR_YUV2BGR_NV12 = 91,
COLOR_YUV2RGB_NV21 = 92,
COLOR_YUV2BGR_NV21 = 93,
COLOR_YUV420sp2RGB = COLOR_YUV2RGB_NV21,
COLOR_YUV420sp2BGR = COLOR_YUV2BGR_NV21,
COLOR_YUV2RGBA_NV12 = 94,
COLOR_YUV2BGRA_NV12 = 95,
COLOR_YUV2RGBA_NV21 = 96,
COLOR_YUV2BGRA_NV21 = 97,
COLOR_YUV420sp2RGBA = COLOR_YUV2RGBA_NV21,
COLOR_YUV420sp2BGRA = COLOR_YUV2BGRA_NV21,
COLOR_YUV2RGB_YV12 = 98,
COLOR_YUV2BGR_YV12 = 99,
COLOR_YUV2RGB_IYUV = 100,
COLOR_YUV2BGR_IYUV = 101,
COLOR_YUV2RGB_I420 = COLOR_YUV2RGB_IYUV,
COLOR_YUV2BGR_I420 = COLOR_YUV2BGR_IYUV,
COLOR_YUV420p2RGB = COLOR_YUV2RGB_YV12,
COLOR_YUV420p2BGR = COLOR_YUV2BGR_YV12,
COLOR_YUV2RGBA_YV12 = 102,
COLOR_YUV2BGRA_YV12 = 103,
COLOR_YUV2RGBA_IYUV = 104,
COLOR_YUV2BGRA_IYUV = 105,
COLOR_YUV2RGBA_I420 = COLOR_YUV2RGBA_IYUV,
COLOR_YUV2BGRA_I420 = COLOR_YUV2BGRA_IYUV,
COLOR_YUV420p2RGBA = COLOR_YUV2RGBA_YV12,
COLOR_YUV420p2BGRA = COLOR_YUV2BGRA_YV12,
COLOR_YUV2GRAY_420 = 106,
COLOR_YUV2GRAY_NV21 = COLOR_YUV2GRAY_420,
COLOR_YUV2GRAY_NV12 = COLOR_YUV2GRAY_420,
COLOR_YUV2GRAY_YV12 = COLOR_YUV2GRAY_420,
COLOR_YUV2GRAY_IYUV = COLOR_YUV2GRAY_420,
COLOR_YUV2GRAY_I420 = COLOR_YUV2GRAY_420,
COLOR_YUV420sp2GRAY = COLOR_YUV2GRAY_420,
COLOR_YUV420p2GRAY = COLOR_YUV2GRAY_420,
COLOR_YUV2RGB_UYVY = 107,
COLOR_YUV2BGR_UYVY = 108,
COLOR_YUV2RGB_Y422 = COLOR_YUV2RGB_UYVY,
COLOR_YUV2BGR_Y422 = COLOR_YUV2BGR_UYVY,
COLOR_YUV2RGB_UYNV = COLOR_YUV2RGB_UYVY,
COLOR_YUV2BGR_UYNV = COLOR_YUV2BGR_UYVY,
COLOR_YUV2RGBA_UYVY = 111,
COLOR_YUV2BGRA_UYVY = 112,
COLOR_YUV2RGBA_Y422 = COLOR_YUV2RGBA_UYVY,
COLOR_YUV2BGRA_Y422 = COLOR_YUV2BGRA_UYVY,
COLOR_YUV2RGBA_UYNV = COLOR_YUV2RGBA_UYVY,
COLOR_YUV2BGRA_UYNV = COLOR_YUV2BGRA_UYVY,
COLOR_YUV2RGB_YUY2 = 115,
COLOR_YUV2BGR_YUY2 = 116,
COLOR_YUV2RGB_YVYU = 117,
COLOR_YUV2BGR_YVYU = 118,
COLOR_YUV2RGB_YUYV = COLOR_YUV2RGB_YUY2,
COLOR_YUV2BGR_YUYV = COLOR_YUV2BGR_YUY2,
COLOR_YUV2RGB_YUNV = COLOR_YUV2RGB_YUY2,
COLOR_YUV2BGR_YUNV = COLOR_YUV2BGR_YUY2,
COLOR_YUV2RGBA_YUY2 = 119,
COLOR_YUV2BGRA_YUY2 = 120,
COLOR_YUV2RGBA_YVYU = 121,
COLOR_YUV2BGRA_YVYU = 122,
COLOR_YUV2RGBA_YUYV = COLOR_YUV2RGBA_YUY2,
COLOR_YUV2BGRA_YUYV = COLOR_YUV2BGRA_YUY2,
COLOR_YUV2RGBA_YUNV = COLOR_YUV2RGBA_YUY2,
COLOR_YUV2BGRA_YUNV = COLOR_YUV2BGRA_YUY2,
COLOR_YUV2GRAY_UYVY = 123,
COLOR_YUV2GRAY_YUY2 = 124,
COLOR_YUV2GRAY_Y422 = COLOR_YUV2GRAY_UYVY,
COLOR_YUV2GRAY_UYNV = COLOR_YUV2GRAY_UYVY,
COLOR_YUV2GRAY_YVYU = COLOR_YUV2GRAY_YUY2,
COLOR_YUV2GRAY_YUYV = COLOR_YUV2GRAY_YUY2,
COLOR_YUV2GRAY_YUNV = COLOR_YUV2GRAY_YUY2,
COLOR_RGBA2mRGBA = 125,
COLOR_mRGBA2RGBA = 126,
COLOR_RGB2YUV_I420 = 127,
COLOR_BGR2YUV_I420 = 128,
COLOR_RGB2YUV_IYUV = COLOR_RGB2YUV_I420,
COLOR_BGR2YUV_IYUV = COLOR_BGR2YUV_I420,
COLOR_RGBA2YUV_I420 = 129,
COLOR_BGRA2YUV_I420 = 130,
COLOR_RGBA2YUV_IYUV = COLOR_RGBA2YUV_I420,
COLOR_BGRA2YUV_IYUV = COLOR_BGRA2YUV_I420,
COLOR_RGB2YUV_YV12 = 131,
COLOR_BGR2YUV_YV12 = 132,
COLOR_RGBA2YUV_YV12 = 133,
COLOR_BGRA2YUV_YV12 = 134,
COLOR_BayerBG2BGR = 46,
COLOR_BayerGB2BGR = 47,
COLOR_BayerRG2BGR = 48,
COLOR_BayerGR2BGR = 49,
COLOR_BayerBG2RGB = COLOR_BayerRG2BGR,
COLOR_BayerGB2RGB = COLOR_BayerGR2BGR,
COLOR_BayerRG2RGB = COLOR_BayerBG2BGR,
COLOR_BayerGR2RGB = COLOR_BayerGB2BGR,
COLOR_BayerBG2GRAY = 86,
COLOR_BayerGB2GRAY = 87,
COLOR_BayerRG2GRAY = 88,
COLOR_BayerGR2GRAY = 89,
COLOR_BayerBG2BGR_VNG = 62,
COLOR_BayerGB2BGR_VNG = 63,
COLOR_BayerRG2BGR_VNG = 64,
COLOR_BayerGR2BGR_VNG = 65,
COLOR_BayerBG2RGB_VNG = COLOR_BayerRG2BGR_VNG,
COLOR_BayerGB2RGB_VNG = COLOR_BayerGR2BGR_VNG,
COLOR_BayerRG2RGB_VNG = COLOR_BayerBG2BGR_VNG,
COLOR_BayerGR2RGB_VNG = COLOR_BayerGB2BGR_VNG,
COLOR_BayerBG2BGR_EA = 135,
COLOR_BayerGB2BGR_EA = 136,
COLOR_BayerRG2BGR_EA = 137,
COLOR_BayerGR2BGR_EA = 138,
COLOR_BayerBG2RGB_EA = COLOR_BayerRG2BGR_EA,
COLOR_BayerGB2RGB_EA = COLOR_BayerGR2BGR_EA,
COLOR_BayerRG2RGB_EA = COLOR_BayerBG2BGR_EA,
COLOR_BayerGR2RGB_EA = COLOR_BayerGB2BGR_EA,
COLOR_BayerBG2BGRA = 139,
COLOR_BayerGB2BGRA = 140,
COLOR_BayerRG2BGRA = 141,
COLOR_BayerGR2BGRA = 142,
COLOR_BayerBG2RGBA = COLOR_BayerRG2BGRA,
COLOR_BayerGB2RGBA = COLOR_BayerGR2BGRA,
COLOR_BayerRG2RGBA = COLOR_BayerBG2BGRA,
COLOR_BayerGR2RGBA = COLOR_BayerGB2BGRA,
COLOR_COLORCVT_MAX = 143
};
使用案例
#python code
#彩色图转灰度读
cvtColorImage = cv2.cvtColor('imagePath',cv2.COLOR_RGB2GRAY)
plt.figure("cvtColorImage")
plt.title("cvtColorImage")
plt.imshow(cvtColorImage)
plt.show()
#C code
#include
using namespace cv;
using namespace std;
int main(int argc, char** argv)
{
Mat src = imread("youImagePath", 1);
Mat cvtMat;
cvtColor(src, cvtMat, COLOR_RGB2GRAY);
namedWindow("src", 0);
imshow("src", src);
namedWindow("cvtMat", 0);
imshow("cvtMat", cvtMat);
waitKey(0);
return 0;
}
效果图
2.函数convertTo
定义：
void cv::Mat::convertTo(OutputArray dst, int rtype, double alpha=1.0, double beta=0.0) const
参数：
dst：输出图像
rtype:转换的数据类型
alpha：尺度变换因子
beta: 附加到尺度变换后的值上的偏移量
作用:将图像从一种数据类型转换为另一种数据类型。
(该函数在opencv-python中并没有体现，可通过numpy函数.astype(np.uint8)来实现)
#python code
import numpy as np
#数据类型 np.uint8/np.uint16/np.uint32/np.uint64
stdImage = np.asarray(stdImage).astype(np.uint8)
#C++ code
#include
using namespace cv;
using namespace std;
int main(int argc, char** argv)
{
Mat src = imread("xx.jpg", 0);
Mat convertToMat;
src.convertTo(convertToMat, CV_32F);
int srcDepth = src.depth();
int newDepth = convertToMat.depth();
cout << "srcDepth=" << srcDepth << endl;
cout << "newDepth=" << newDepth << endl;
system("pause");
return 0;
}
3.函数split (将多通道图像分离为每个通道)
定义：
void split(const Mat& src, Mat* mvbegin);
void split(InputArray m, OutputArrayOfArrays mv);
def split(m, mv=None)
参数：
src：输入图像
m：输入图像
mvbegin:输出每个通道
mv：输出每个通道
使用案例
#python code
image=cv2.imread('imagepath')
SplitImage1,SplitImage2,SplitImage3 = cv2.split(image)
#C++ code
#include
using namespace cv;
using namespace std;
int main(int argc, char** argv)
{
Mat src = imread("xxx.jpg", 1);
vector<Mat> vecMat;
split(src,vecMat);
namedWindow("src", 0);
imshow("src", src);
for (int i = 0; i < vecMat.size(); i++)
{
namedWindow(to_string(i), 0);
imshow(to_string(i), vecMat[i]);
}
waitKey(0);
return 0;
}
效果图
4.函数merge 将图片不同通道合并
定义：
void merge(const Mat* mv, size_t count, OutputArray dst);
void merge(InputArrayOfArrays mv, OutputArray dst);
def merge(mv, dst=None)
参数：
mv：输入的每个单通道图像
count：输入图像的数量
dst：输出的多通道
一般用于多个单通图片合并成多通道彩色图
python code
#python code
image=cv2.imread('imagepath')
SplitImage1,SplitImage2,SplitImage3 = cv2.split(image)
new_image_merge=cv2.merge([SplitImage1,SplitImage2,SplitImage3])
plt.figure("new_image_merge")
plt.title("new_image_merge")
plt.imshow(new_image_merge)
plt.show()
#C++ code
#include
using namespace cv;
using namespace std;
int main(int argc, char** argv)
{
Mat src = imread("xxxx.jpg", 1);
vector<Mat> vecMat;
split(src, vecMat);
Mat mergeMat;
merge(vecMat, mergeMat);
namedWindow("mergeMat", 0);
imshow("mergeMat", mergeMat);
waitKey(0);
return 0;
}
5.函数extractChannel 指定抽取多通道图像的某个通道
定义：
void extractChannel(InputArray src, OutputArray dst, int coi);
def extractChannel(src, coi, dst=None)
参数：
src：输入的多通道图像
dst：输出指定通道图像
coi：输入图像的指定通道
使用案例
#python code
image=cv2.imread('imagepath')
channel0=cv2.extractChannel(image,0)
channel1=cv2.extractChannel(image,1)
channel2=cv2.extractChannel(image,2)
#C++ code
#include
using namespace cv;
using namespace std;
int main(int argc, char** argv)
{
Mat src = imread("xxx.jpg", 1);
Mat dst;
extractChannel(src, dst, 1);
namedWindow("dst", 0);
imshow("dst", dst);
waitKey(0);
return 0;
}
6.函数applyColorMap 灰度图转伪彩色图
定义：
void applyColorMap(InputArray src, OutputArray dst, int colormap);
def applyColorMap(src, colormap, dst=None)
参数：
src：输入的多通道图像
dst：输出指定通道图像
colormap：颜色模式，可以取下列枚举值(具体效果大家自己可以手动尝试)
enum ColormapTypes
{
COLORMAP_AUTUMN = 0,
COLORMAP_BONE = 1,
COLORMAP_JET = 2,
COLORMAP_WINTER = 3,
COLORMAP_RAINBOW = 4,
COLORMAP_OCEAN = 5,
COLORMAP_SUMMER = 6,
COLORMAP_SPRING = 7,
COLORMAP_COOL = 8,
COLORMAP_HSV = 9,
COLORMAP_PINK = 10,
COLORMAP_HOT = 11,
COLORMAP_PARULA = 12
};
使用案例
#python code
image=cv2.imread('imagepath')
SplitImage1,SplitImage2,SplitImage3 = cv2.split(image)
applyColorMapImage = cv2.applyColorMap(SplitImage1,cv2.COLORMAP_AUTUMN)
plt.figure("applyColorMapImage")
plt.title("applyColorMapImage")
plt.imshow(applyColorMapImage)
plt.show()
#C++ code
#include
using namespace cv;
using namespace std;
int main(int argc, char** argv)
{
Mat src = imread("xxx.jpg", 0);
Mat dst(src.size(), src.depth());
applyColorMap(src, dst, 1);
namedWindow("dst", 0);
imshow("dst", dst);
waitKey(0);
return 0;
}
效果图
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五：OpenCV图像变换与增强一(C++/python)
Original: https://blog.csdn.net/leifengpeng/article/details/126236743
Author: fplei
Title: 三：OpenCV图片颜色通道数据转换
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