Question

我创建了一种拼接算法，可以将许多图像拼接在一起。它没有使用捆绑调整，但这是后来的补充。

在找到两个图像之间的单应性后，我正在缝合我做一系列翻译，透视变换和warpPerspectives来实现我的最终结果。以下两个图像是两个图像拼接，第一个是从左到右传递的图像，后者是从右到左传递的图像。每个图像包括关于为缝合图像而创建的平移矩阵的信息。结果图像是空白图像的新填充大小，其中包含拼接图像（您所看到的图像）。

Image 1: Min x 478.711 Min y 3.16 Max x 1853.66 Max y 1449.42
Image 2: Min x 0 Min y 0 Max x 1200 Max y 900
Result Image: Min x 0 Min y 0 Max x 1853.66 Max y 1449.42
[1, 0, 0;
 0, 1, 0;                                                                       Stitch 2
 0, 0, 1]

Image 1: Min x -671.462 Min y -461.816 Max x 652.656 Max y 655.324
Image 2: Min x 0 Min y 0 Max x 1200 Max y 900
Result Image: Min x -671.462 Min y -461.816 Max x 1200 Max y 900
[1, 0, 672;
 0, 1, 462;                                                                     Stitch2/Rev
 0, 0, 1]

看起来效果很好，非常棒。然而，当我在3个图像中运行代码管道时，我会得到奇怪的线条，黑色背景应该是，然后我的填充开始失败。再次参考图像和翻译。

---------------------
Image 1: Min x 390.279 Min y 72.4343 Max x 1658.93 Max y 1110.17
Image 2: Min x 0 Min y 0 Max x 1200 Max y 900
Result Image: Min x 0 Min y 0 Max x 1658.93 Max y 1110.17
[1, 0, 0;
 0, 1, 0;
 0, 0, 1]

Image 1: Min x 439.817 Min y -20.4711 Max x 2205.2 Max y 1288.93
Image 2: Min x 0 Min y 0 Max x 1200 Max y 900
Result Image: Min x 0 Min y -20.4711 Max x 2205.2 Max y 1288.93
[1, 0, 0;
 0, 1, 21;
 0, 0, 1]
---------------------

本节的代码如下。任何帮助表示赞赏。

Mat result, descriptors_updated;
    vector<Point2f> fourPointImage1, fourPointImage2, image1dst, image2dst;
    vector<KeyPoint> keypoints_updated;
    float min_x, min_y, max_x, max_y, result_x, result_y, img1_min_x, img1_min_y, img2_min_x, img2_min_y,img1_max_x, img1_max_y, img2_max_x, img2_max_y, result_min_x, result_max_x, result_min_y, result_max_y;

    //get four corners of image MATs
    fourPointImage1 = fourCorners(image1);
    fourPointImage2 = fourCorners(image2);

    //get the min and max corners
    tie(min_x, min_y, max_x, max_y) = minMaxCorners(fourPointImage1);

    //- Htr use to map image one to result in line with the already warped image two
    Mat Htr = Mat::eye(3,3,CV_64F);
    if (min_x < 0){
        max_x = image2.size().width - min_x;
        Htr.at<double>(0,2)= -min_x;
    }
    if (min_y < 0){
        max_y = image2.size().height - min_y;
        Htr.at<double>(1,2)= -min_y;
    }

    //- Need to create a padded blank image to accomodate stitched images.
    //- Must first determine where the translations of the two images will end up to determine if shift is needed and how much to pad blank image
    perspectiveTransform(fourPointImage1, image1dst, Htr*homography);
    perspectiveTransform(fourPointImage2, image2dst, Htr);

    //- Now determine what is out of bounds
    //New coordinates for image 1
    tie(img1_min_x, img1_min_y,img1_max_x,img1_max_y) = minMaxCorners(image1dst);
    cout << "Image 1: Min x " << img1_min_x << " Min y " << img1_min_y << " Max x " << img1_max_x << " Max y " << img1_max_y << endl;

    //New coordinates for iamge 2
    tie(img2_min_x, img2_min_y,img2_max_x,img2_max_y) = minMaxCorners(image2dst);
    cout << "Image 2: Min x " << img2_min_x << " Min y " << img2_min_y << " Max x " << img2_max_x << " Max y " << img2_max_y << endl;

    //determine bounding area for resulting images
    result_min_x = min(img1_min_x, img2_min_x);
    result_max_x = max(img1_max_x, img2_max_x);
    result_min_y = min(img1_min_y, img2_min_y);
    result_max_y = max(img1_max_y, img2_max_y);

    cout << "Result Image: Min x " << result_min_x << " Min y " << result_min_y << " Max x " << result_max_x << " Max y " << result_max_y << endl;

    //Determine size of padded result (blank image) to be used for stitching
    result_x = (abs(floor(result_min_x)) + abs(ceil(result_max_x)));
    result_y = (abs(floor(result_min_y)) + abs(ceil(result_max_y)));

    result = Mat(Size(result_x,result_y), CV_32FC1,Scalar(0,0,0));

    //-Move the images to the postiive by creating a matrix to represent the translation
    int anchor_x, anchor_y = 0;
    Mat translation = Mat::eye(3,3,CV_64F);
    if(result_min_x < 0){
        anchor_x = (int) floor(result_min_x);
        translation.at<double>(0,2) -= anchor_x;
    }
    if(result_min_y < 0){
        anchor_y = (int) floor(result_min_y);
        translation.at<double>(1,2) -= anchor_y;
    }

    cout << translation << endl;

    //Warp each image accordingly to the new padded result image
    warpPerspective(image2, result, translation, result.size(), INTER_LINEAR, BORDER_TRANSPARENT,   0);
    warpPerspective(image1, result, (translation*homography), result.size(), INTER_LINEAR, BORDER_TRANSPARENT,0);

vector<Point2f> fourCorners(Mat image){
    vector<Point2f> corners;
    corners.push_back(Point2f (0,0));
    corners.push_back(Point2f (image.size().width,0));
    corners.push_back(Point2f (0, image.size().height));
    corners.push_back(Point2f (image.size().width, image.size().height));
    return(corners);
}

tuple<float, float, float, float> minMaxCorners(vector<Point2f> imageMatrix){
    float min_x1, min_x2, min_y1, min_y2, max_x1, max_x2, max_y1, max_y2,img_min_x, img_min_y, img_max_x, img_max_y;
    min_x1 = min(imageMatrix.at(0).x, imageMatrix.at(1).x);
    min_x2 = min(imageMatrix.at(2).x, imageMatrix.at(3).x);
    min_y1 = min(imageMatrix.at(0).y, imageMatrix.at(1).y);
    min_y2 = min(imageMatrix.at(2).y, imageMatrix.at(3).y);
    max_x1 = max(imageMatrix.at(0).x, imageMatrix.at(1).x);
    max_x2 = max(imageMatrix.at(2).x, imageMatrix.at(3).x);
    max_y1 = max(imageMatrix.at(0).y, imageMatrix.at(1).y);
    max_y2 = max(imageMatrix.at(2).y, imageMatrix.at(3).y);
    img_min_x = min(min_x1, min_x2);
    img_min_y = min(min_y1, min_y2);
    img_max_x = max(max_x1, max_x2);
    img_max_y = max(max_y1, max_y2);
    return{img_min_x,img_min_y, img_max_x, img_max_y };
}

编辑我不确定，但有时只会出现，如下图所示。

Opencv图像翻译工件（C ++）

0 个答案: