java - 用于校正 FishEye 镜头的桶形畸变校正算法 - 无法使用 Java 实现

Question

我有大量用鱼眼镜头拍摄的照片。因为我想对照片进行一些图像处理(例如边缘检测)，所以我想消除严重影响结果的桶形失真。

经过一些研究和大量阅读文章后，我发现了这个 page : 他们描述了一种算法(和一些公式)来解决这个问题。

M = a *rcorr^3 + b * rcorr^2 + c * rcorr + d
rsrc = (a * rcorr^3 + b * rcorr^2 + c * rcorr + d) * rcorr

rsrc = distance of a pixel from the center of the source image
rcorr = distance of a pixel from the center in the corrected image
a,b,c = distortion of image d = linear scaling of image

我使用了这些公式并尝试在 Java 应用程序中实现它。不幸的是它不起作用，我没能让它起作用。 “修正后”的图像与原始照片完全不同，而是在中间显示了一些神秘的圆圈。看这里:

http://imageshack.us/f/844/barreldistortioncorrect.jpg/ (这曾经是一头白牛在蓝墙前的照片)

这是我的代码:

protected int[] correction(int[] pixels) {

    //
    int[] pixelsCopy = pixels.clone();

    // parameters for correction
    double paramA = 0.0; // affects only the outermost pixels of the image
    double paramB = -0.02; // most cases only require b optimization
    double paramC = 0.0; // most uniform correction
    double paramD = 1.0 - paramA - paramB - paramC; // describes the linear scaling of the image

    //
    for(int x = 0; x < dstView.getImgWidth(); x++) {
        for(int y = 0; y < dstView.getImgHeight(); y++) {

            int dstX = x;
            int dstY = y;

            // center of dst image
            double centerX = (dstView.getImgWidth() - 1) / 2.0;
            double centerY = (dstView.getImgHeight() - 1) / 2.0;

            // difference between center and point
            double diffX = centerX - dstX;
            double diffY = centerY - dstY;
            // distance or radius of dst image
            double dstR = Math.sqrt(diffX * diffX + diffY * diffY);

            // distance or radius of src image (with formula)
            double srcR = (paramA * dstR * dstR * dstR + paramB * dstR * dstR + paramC * dstR + paramD) * dstR;

            // comparing old and new distance to get factor
            double factor = Math.abs(dstR / srcR);
            // coordinates in source image
            double srcXd = centerX + (diffX * factor);
            double srcYd = centerY + (diffX * factor);

            // no interpolation yet (just nearest point)
            int srcX = (int)srcXd;
            int srcY = (int)srcYd;

            if(srcX >= 0 && srcY >= 0 && srcX < dstView.getImgWidth() && srcY < dstView.getImgHeight()) {

                int dstPos = dstY * dstView.getImgWidth() + dstX;
                pixels[dstPos] = pixelsCopy[srcY * dstView.getImgWidth() + srcX];
            }
        }
    }

    return pixels;
}

我的问题是:
1)这个公式对吗？
2) 我把那个公式变成一个软件是不是犯了一个错误？
3) 还有其他算法(例如 How to simulate fisheye lens effect by openCV? 或 wiki/Distortion_(optics))，它们更好吗？

感谢您的帮助!

Answer 1

您遇到的主要错误是算法指定 r_corr 和 r_src 以 min((xDim-1)/2, (yDim-1)/2) 为单位。需要这样做来规范化计算，以便参数值不依赖于源图像的大小。使用代码，您需要为 paramB 使用更小的值，例如paramB = 0.00000002(对于尺寸为 2272 x 1704 的图像)对我来说效果很好。

您在计算与中心的差异时也有一个错误，导致生成的图像与源图像相比旋转了 180 度。

修复这两个错误应该会给你这样的东西:

protected static int[] correction2(int[] pixels, int width, int height) {
    int[] pixelsCopy = pixels.clone();

    // parameters for correction
    double paramA = -0.007715; // affects only the outermost pixels of the image
    double paramB = 0.026731; // most cases only require b optimization
    double paramC = 0.0; // most uniform correction
    double paramD = 1.0 - paramA - paramB - paramC; // describes the linear scaling of the image

    for (int x = 0; x < width; x++) {
        for (int y = 0; y < height; y++) {
            int d = Math.min(width, height) / 2;    // radius of the circle

            // center of dst image
            double centerX = (width - 1) / 2.0;
            double centerY = (height - 1) / 2.0;

            // cartesian coordinates of the destination point (relative to the centre of the image)
            double deltaX = (x - centerX) / d;
            double deltaY = (y - centerY) / d;

            // distance or radius of dst image
            double dstR = Math.sqrt(deltaX * deltaX + deltaY * deltaY);

            // distance or radius of src image (with formula)
            double srcR = (paramA * dstR * dstR * dstR + paramB * dstR * dstR + paramC * dstR + paramD) * dstR;

            // comparing old and new distance to get factor
            double factor = Math.abs(dstR / srcR);

            // coordinates in source image
            double srcXd = centerX + (deltaX * factor * d);
            double srcYd = centerY + (deltaY * factor * d);

            // no interpolation yet (just nearest point)
            int srcX = (int) srcXd;
            int srcY = (int) srcYd;

            if (srcX >= 0 && srcY >= 0 && srcX < width && srcY < height) {
                int dstPos = y * width + x;
                pixels[dstPos] = pixelsCopy[srcY * width + srcX];
            }
        }
    }

    return pixels;
}

有了这个版本，您可以使用现有镜头数据库(例如 LensFun)中的参数值(尽管您需要翻转每个参数的符号)。描述该算法的页面现在可以在 http://mipav.cit.nih.gov/pubwiki/index.php/Barrel_Distortion_Correction 找到。