voidsalt(Mat &image, int n){
for (int k = 0; k < n; k++){
int i = rand() % image.cols;
int j = rand() % image.rows;
// rand() ranges from 0 to int.max if the denominator is large its not
// uniform distribution
if (image.channels() == 1){
// 255 means white
image.at<uchar>(j, i) = 255;
}
else if (image.channels() == 3){
//color image has 3 channels : blue yellow red in scale form
image.at<Vec3b>(j, i)[0] = 255;
image.at<Vec3b>(j, i)[1] = 255;
image.at<Vec3b>(j, i)[2] = 255;
}
}
}
Then
// reducethe quality of each pixel
voidcolorReduce(Mat &image, int div = 64){
int nl = image.rows;
int nc = image.cols*image.channels();
for (int i = 0; i < nl; i++){
uchar* data = image.ptr<uchar>(i);
// .ptr is more efficient than .at
for (int j = 0; j < nc; j++){
data[j] = data[j] / div*div + div / 2;
//another way is to use bit operator which is a very efficientalternative
// data[j]=(data[j]&(0xFF<<n))+div/2;
}
}
}
2/4/2015 11:34 AM - Screen Clipping
If u wanna haveinput and output in the method
It can be wirttenlike void colorReduce(const Mat &image, Mat &result, int div=64);
To a continuous line
Image.reshape(1,rows*cols);
channel newrows
&image.at(j,i)
Means data =image.data+ j*image.step+i*image.elemSize()
Using iterator toaccess pixels
Mat_<Vec3b>::iteratorit = image.begin<Vec3b>(), itend = image.end<Vec3b>();
It++
(*it)[0]
Its convenient but the pointer type is the fastest
In the following waywe can count time is ms;
double duration = static_cast<double>(getTickCount());
colorReduce(image);
duration = static_cast<double>(getTickCount()) - duration;
duration /= getTickFrequency();
void sharpen(Mat &image,Mat &result){
result.create(image.size(), image.type());
for (int i = 1; i < image.rows-1;i++)
{
const uchar* previous = image.ptr<const uchar>(i - 1);
const uchar* current = image.ptr<const uchar>(i);
const uchar* next = image.ptr< const uchar>(i + 1);
uchar* output = result.ptr<uchar>(i);
for (int j = 1; j < image.cols - 1; j++){
*output++ =saturate_cast<uchar>( current[j] * 5 - current[j -1] - current[j + 1] - previous[j] - next[j]);
//saturate means 0<= uchar<=255
}
}
result.row(0).setTo(Scalar(0));
result.row(result.rows-1).setTo(Scalar(0));
result.col(0).setTo(Scalar(0));
result.col(result.cols-1).setTo(Scalar(0));
// deal with the whole row or column
}
Add onepic to another
// c[i]=a[i]+b[i];
cv::add(imageA,imageB,resultC);
// c[i]= a[i]+k;
cv::add(imageA,cv::Scalar(k),resultC);
// c[i]= k1*a[1]+k2*b[i]+k3;
cv::addWeighted(imageA,k1,imageB,k2,k3,resultC);
// c[i]= k*a[1]+b[i];
cv::scaleAdd(imageA,k,imageB,resultC);
Add weightis overloaded
result=0.7*image1+0.9*image2;
image=(image&cv::Scalar(mask,mask,mask))
+cv::Scalar(div/2,div/2,div/2);
Split andmerge
// create vector of 3 images
std::vector<cv::Mat> planes;
// split 1 3-channel image into 3 1-channelimages
cv::split(image1,planes);
// add to blue channel
planes[0]+= image2;
// merge the 3 1-channel images into 13-channel image
cv::merge(planes,result);
ROI
Rect(200,250,logoImage.cols,logoImage.rows)
cv::MatimageROI= image(cv::Range(270,270+logo.rows),
cv::Range(385,385+logo.cols))
image.colRange(start,end);
intmain(){
Mat logo= imread("logo.jpg");
Mat image = imread("rain.jpg");
//the same size
Mat ROI;
Mat result;
imshow("old", image);
result.create(image.size(), image.type());
double duration = static_cast<double>(getTickCount());
//
ROI = image(Rect(0, 0, logo.cols,logo.rows));
addWeighted(logo, 0.3,ROI, 1.0, 0.0,ROI);
//
duration = static_cast<double>(getTickCount()) - duration;
duration /= getTickFrequency();
cout << duration;
imshow("new",image);
waitKey(0);
}
