Mat object channel operation

Image channel separation

The implementation code is as follows

split(Mat m,List<Mat> mv)//Channel separation

Here is a code to show

After getting channels of Mat object, if the number of channels is greater than 1, then channel separation can be used

//First get the number of channels width and height of the image
int channels = m1.channels();
if(channels>1){
    List<Mat> ms = new ArrayList<>();//Mat set
    Core.split(m1,ms);//Channel separation
    int i = 0;//subscript
    for (Mat mat  : ms){
        HighGui.imshow(String.valueOf(i++)+"passageway",mat);
    }
}

Operation result:

Image channel merge

The implementation code is as follows

merge(List<Mat> mv,Mat dst)//Channel merging

The following code shows that the separated channels above are merged

Mat hebing = new Mat();//create object
Core.merge(ms,hebing);//Merge channel

HighGui.imshow("After channel merging",hebing);//Exhibition

Arithmetic operation

Mat objects can be added, subtracted, multiplied, and divided. The most common methods are as follows

add(Mat src1,Mat src2 ,Mat dst)
subtract(Mat src1,Mat src2 ,Mat dst)
multiply(Mat src1,Mat src2 ,Mat dst)
divide(Mat src1,Mat src2 ,Mat dst)

Parameter interpretation:

• src1: first Mat object entered
• src2: second Mat object entered
• dst: object output after operation

When src1 and src2 are Mat, it should be noted that the size and type of the two images must be the same

Let me show you an example

Mat m1 = Imgcodecs.imread("C:\\test\\256_256_t1.png" );
Mat m2 = Imgcodecs.imread("C:\\test\\256_256_t2.png" );
//The two sizes you read are exactly the same.
HighGui.imshow("256_256_t1.jpg",m1);
HighGui.imshow("256_256_t2.jpg",m2);

//Addition operation
Mat dst1 = new Mat();
Core.add(m1,m2,dst1);
HighGui.imshow("Addition operation",dst1);
//Subtraction operation
Mat dst2 = new Mat();
Core.subtract(m1,m2,dst2);
HighGui.imshow("Subtraction operation",dst2);
//Multiplication operation
Mat dst3 = new Mat();
Core.multiply(m1,m2,dst3);
HighGui.imshow("Multiplication operation",dst3);
//Division operation
Mat dst4 = new Mat();
Core.divide(m1,m2,dst4);
HighGui.imshow("Division operation",dst4);

As for the results
Maybe I'm too illiterate to think of any use
I feel that only addition and subtraction can be used, multiplication and division will not know

But then I tried Scalar objects in pure colors

I finally see a glimmer of hope here. It's useless if I don't feel multiplication and division

Here is the implementation code

Mat m1 = Imgcodecs.imread("C:\\test\\256_256_t1.png" );

Scalar m2 = new Scalar(10,10,10);

HighGui.imshow("256_256_t1.jpg",m1);
//Addition operation
Mat dst1 = new Mat();
Core.add(m1,m2,dst1);
HighGui.imshow("Addition operation",dst1);
//Subtraction operation
Mat dst2 = new Mat();
Core.subtract(m1,m2,dst2);
HighGui.imshow("Subtraction operation",dst2);
//Multiplication operation
Mat dst3 = new Mat();
Core.multiply(m1,m2,dst3);
HighGui.imshow("Multiplication operation",dst3);
//Division operation
Mat dst4 = new Mat();
Core.divide(m1,m2,dst4);
HighGui.imshow("Division operation",dst4);

Adjust brightness and contrast

The linking and contrast of images are two basic attributes of images,

• Brightness for RGB color, the larger the corresponding RGB value is, the closer it is to 255, otherwise, the smaller it is, the closer it is to 0

• Contrast describes the difference between image colors

Adjusting the brightness is to use the Scalar object for the m2 above (the second demonstration)

Poof!!! The above arithmetic operations are used to adjust brightness and contrast

Got the code and the graph I also did not send, is above thing!!!