使用Open CV和C ++将彩色图像分成三个通道？

问题描述

我是Open CV的新手，所以如果我的问题听起来很愚蠢，请原谅我。因此，我正在研究使用拆分功能将BGR通道分割到各个通道的新概念。我正在阅读这个程序，我无法理解代码。所以，任何人都可以向我解释以下代码行，因为我真的很想理解这个概念。



我根本不理解创建蓝色通道部分。请有人能解释一下吗？



src = imread（pic.png）;



vector< mat> spl（3）;

split（src，spl）;



Mat empty_image = Mat :: zeros（src.rows，src。 cols，CV_8UC1）;

Mat result_blue（src.rows，src.cols，CV_8UC3）; //注意这里的3个频道！



//创建蓝色频道



Mat in1 [] = {spl [0]，empty_image，empty_image};

int from_to1 [] = {0,0,1,1,2,2};

mixChannels（in1， 3，& result_blue，1，from_to1,3）;



imshow（blue image，result_blue）;

I am new to Open CV, so please forgive me if my question sounds stupid. So, i was studying about this new concept of splitting a BGR channel to individual channels using the split function. I was reading this program and i could not understand the code. So, please can anyone explain me the following line of code as i am really wanted to understand the concept.

I did not understand the create blue channel part at all. Please can anyone explain me a bit?

src = imread("pic.png");

vector<mat> spl(3);
split(src,spl);

Mat empty_image = Mat::zeros(src.rows, src.cols, CV_8UC1);
Mat result_blue(src.rows, src.cols, CV_8UC3); // notice the 3 channels here!

// Create blue channel

Mat in1[] = { spl[0], empty_image, empty_image };
int from_to1[] = { 0,0, 1,1, 2,2 };
mixChannels( in1, 3, &result_blue, 1, from_to1, 3 );

imshow("blue image", result_blue);

推荐答案

src = imread("pic.png");
	// . read image file 'pic.png' and save data to variable 'src'
	// . at this time, 'src' will have all informations about
	// . 'pic.png' such as bit count, width, height, plane count,
	// . all pixel values
	// . pixel values will be stored as 3-dimensions array, i.e
	// . src[x][y][i] = i th channel pixel-value for coordinate (x,y)
	// . here 0 : R, 1 : G, 2 : B, or inversely
	// . 0 : B, 1 : G, 2 : R
	
vector spl(3);
	// . vector is array that has N columns and one row.
	// . above means spl is array that has N columns and 3 rows.
	
split(src,spl);
	// . split src into spl
	// . this resuls spl[0] = B space
	// . 			 spl[1] = G space
	// .			 spl[2] = R space

Mat empty_image = Mat::zeros(src.rows, src.cols, CV_8UC1);
	// . initialize empty_image as one channel image which size is
	// . [ src.rows * src.cols ]
	// . here CV_8UC1 is opencv definition value and means that
	// . empty_image will be created as 1 channel matrix.
	// . CV_8UC3 that can be found below line menas that
	// . result_blue will be created as 3 channel matrix.
	
Mat result_blue(src.rows, src.cols, CV_8UC3); // notice the 3 channels here!

// Create blue channel

Mat in1[] = { spl[0], empty_image, empty_image };
	// . in1[] is 3 channel image
	// . channel 1 - B space
	// . channel 2, 3 - zeros
	
int from_to1[] = { 0,0, 1,1, 2,2 };
	// . color-space convertion mapping
	
mixChannels( in1, 3, &result_blue, 1, from_to1, 3 );
	// . here from_to1 is mapping that means that there are no color-space
	// . convertion because from_to1[] is equal-value-mapping.
	// . result_blue[0] = in1[0] = spl[0] = B space
	// . result_blue[1] = in1[1] = zero
	// . result_blue[2] = in1[2] = zero

imshow("blue image", result_blue);
	// . show image on window named "blue image"

我希望我的话能帮到你。

I wish my words would help you.

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