我想使用 OpenCV 锐化我的图像，我在网上查看了一个对灰度图像执行锐化的示例，我尝试了一下，效果很好。然而，我现在正尝试做同样的事情，但使用 RGB 颜色，所以我在三个 channel 上分别执行相同的功能，但它没有给我任何结果图像与原始图像完全一样。

#include "Sharpening.h"
using namespace std;

Sharpening::Sharpening() {
}

Sharpening::~Sharpening() {
}

IplImage* Sharpening::laplace(IplImage* channel) {

    CvSize size = cvSize(channel->width, channel->height);

    IplImage* temp = cvCreateImage(size, IPL_DEPTH_8U, 1);

    IplImage* lapl = cvCreateImage(size, IPL_DEPTH_8U, 1);

    int width = size.width;

    int height = size.height;

    cvConvertScale(channel, temp, 1.0);

    CvMat* ker = cvCreateMat(3, 3, CV_32FC1);

    cvSet(ker, cvScalarAll(-1.0));

    cvSet2D(ker, 1, 1, cvScalarAll(15.0));

    cout << "this is been executed";

    cvFilter2D(temp, lapl, ker);

    cvReleaseMat(&ker);

    double maxv = 0.0;

    float maxFloat = 1.79769e+308;

    double minv = maxFloat;

    cvMinMaxLoc(lapl, &minv, &maxv);


    for (int i = 0; i < width * height; i++) {

        double lap_val = cvGet1D(lapl, i).val[0];

        int v = (int) ((255.0 * lap_val / maxv) + 0.5); // this calculation does nothing particularly

        cvSet1D(temp, i, cvScalarAll(v));
    }

    maxv = 0.0;

    cvMinMaxLoc(channel, &minv, &maxv);

    for (int i = 0; i < width * height; i++) {

        double val = cvGet1D(channel, i).val[0];
        int v = (int) ((255.0 * val / maxv) + 0.5);

        cvSet1D(channel, i, cvScalarAll(v));
    }

    cvReleaseImage(&temp);
    cvReleaseImage(&lapl);
    cvReleaseMat(&ker);

    return channel;
} // end of function

int Sharpening::calculateLoop(int number) {
    int value = 2;
    for (int i = 0; i < 10; i++) {
        number = number * value;
        cout << number << endl;
    }

    return number;
}

//======================================================================================

int Sharpening::SharpenColored(Sharpening sharp) {

    int key = 0;

    CvCapture *capture = 0;

    IplImage* frame = 0;

    cvNamedWindow("deblur", CV_WINDOW_AUTOSIZE);

    cvNamedWindow("deblur2", CV_WINDOW_AUTOSIZE);

    cvNamedWindow("origional", CV_WINDOW_AUTOSIZE);

    // initialize camera
    capture = cvCaptureFromCAM(0); //capture from a camera

    //capture = cvCaptureFromAVI("jabelH2.avi");

    //frame = cvQueryFrame(capture);

    if (!cvGrabFrame(capture)) { // capture a frame
        printf("Could not grab a frame\n\7");
        exit(0);
    }

    frame = cvQueryFrame(capture);

    CvSize imageSize1 = cvSize(frame->width, frame->height);

    IplImage* R = cvCreateImage(imageSize1, IPL_DEPTH_8U, 1);

    IplImage* G = cvCreateImage(imageSize1, IPL_DEPTH_8U, 1);

    IplImage* B = cvCreateImage(imageSize1, IPL_DEPTH_8U, 1);

    IplImage* R2 = cvCreateImage(imageSize1, IPL_DEPTH_8U, 1);

    IplImage* G2 = cvCreateImage(imageSize1, IPL_DEPTH_8U, 1);

    IplImage* B2 = cvCreateImage(imageSize1, IPL_DEPTH_8U, 1);

    IplImage* source = cvCreateImage(imageSize1, IPL_DEPTH_8U, 3);

    IplImage* result = cvCreateImage(imageSize1, IPL_DEPTH_8U, 3);

    IplImage* result2 = cvCreateImage(imageSize1, IPL_DEPTH_8U, 3);

    QFuture<IplImage*> future1;

    QFuture<IplImage*> future2;

    QFuture<IplImage*> future3;

    while (key != 'q') {
        // get a frame

        frame = cvQueryFrame(capture);

        // always check
        if (!frame)
            break;

        source = frame;

        cvSplit(frame, B, G, R, NULL);

        future1 = QtConcurrent::run(sharp, &Sharpening::laplace, R);

        future2 = QtConcurrent::run(sharp, &Sharpening::laplace, G);

        future3 = QtConcurrent::run(sharp, &Sharpening::laplace, B);

        R2 = future1.result();

        G2 = future2.result();

        B2 = future3.result();

        cvMerge(B2, G2, R2, NULL, result);

        cvAdd(source, result, result2, NULL);
        cvShowImage("origional", source);
        cvShowImage("deblur", R2);
        cvShowImage("deblur2", G2);

        key = cvWaitKey(1);
    } //end of while

    cvDestroyWindow("deblur");
    cvDestroyWindow("deblur2");
    cvDestroyWindow("origional");
    cvReleaseImage(&R);
    cvReleaseImage(&source);
    cvReleaseImage(&R2);
    cvReleaseImage(&G);
    cvReleaseImage(&G2);
    cvReleaseImage(&B);
    cvReleaseImage(&B2);
    cvReleaseImage(&result);
    cvReleaseImage(&result2);
    cvReleaseCapture(&capture);
    delete future1;
    delete future2;
    delete future3;

    return 0;
} //end of function

//======================================================================================

int main(int argc, char *argv[]) {
    Sharpening sh;
    sh.SharpenColored(sh);
}

最佳答案

I am now trying to do the same but with RGB colors so I am performing the same functionality

检查你的假设!我不认为你在做同样的事情。我不知道openCV 很好，但是你没有对你的临时图像做任何事情，所以没有理由改变 channel 图像!您应该在原始图像中设置临时图像的结果，也许是这样的:

for (int i = 0; i < width * height; i++) {

    double lap_val = cvGet1D(lapl, i).val[0]; // get modified image data

    int v = (int) ((255.0 * lap_val / maxv) + 0.5); // scale to 0 255
    cvSet1D(channel, i, cvScalarAll(v)); // store in original image
}

或者您可以获取原始代码，并对其进行注释以解释每个 cvImage 包含的内容，并查看在您的应用中重用它时遗漏了什么。

关于c++ - 使用 openCV 锐化视频图像，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/8396140/