目前我正在开发一个Java项目，该项目将缝合从无人机安装的GoPro中获取的图像。随着图像也出现GPS数据，分配给每个相机拍摄：
Latitude Longitude Altitude Roll Pitch Yaw
CAM, 467270000, 1895, 58.3705557, 31.0359788, 131.30, 109.88, 0.73, -10.70, 172.79
CAM, 467273600, 1895, 58.3702211, 31.0354466, 126.43, 105.01, -1.02, -4.61, 218.37
CAM, 467277400, 1895, 58.3699252, 31.0348309, 127.61, 106.19, -6.50, -2.75, 233.71
CAM, 467281400, 1895, 58.3695767, 31.0342934, 120.87, 99.45, -0.52, 7.95, 229.61
CAM, 467284800, 1895, 58.3692659, 31.0337095, 131.80, 110.38, -8.02, 6.47, 225.28
CAM, 467288800, 1895, 58.3689556, 31.0331251, 132.72, 111.30, -5.50, -7.32, 223.22
CAM, 467292800, 1895, 58.3685826, 31.0326798, 132.01, 110.59, -16.65, 0.24, 215.20
CAM, 467297400, 1895, 58.3682075, 31.0330935, 127.13, 105.71, -37.07, 9.32, 143.64
CAM, 467300600, 1895, 58.3683265, 31.0339103, 132.22, 110.80, -24.37, 3.29, 102.24
CAM, 467303800, 1895, 58.3686659, 31.034442, 131.46, 110.04, -9.07, -1.69, 76.16
这是我用于算法的输入数据。首先，我创建了ArrayList latitude，longitude，altitude和
distanceList（连续2张图像的中心之间的距离）; azimuthList（图片的方位角）; coordinateAngleList（下一个图像相对于前一个图像的角度）; pixelSizeList（以米为单位的一个像素的大小）。以下是我用来计算列出值的算法：
distanceList和azimuthList：
private static double calculateDistanceOrAzimuthAngle(Double llat1, Double llong1, Double llat2, Double llong2, String mode) {
double pi = Math.PI;
//===== Earth radius in meters
int rad = 6372795;
//===== Coordinates in radians
double phi1 = Math.toRadians(llat1);
double phi2 = Math.toRadians(llat2);
double lam1 = Math.toRadians(llong1);
double lam2 = Math.toRadians(llong2);
double lambda = lam2 - lam1;
//===== Cos and Sin of latitudes and delta of longitudes
double c11 = Math.cos(phi1);
double c12 = Math.cos(phi2);
double s11 = Math.sin(phi1);
double s12 = Math.sin(phi2);
double cdelta = Math.cos(lambda);
double sdelta = Math.sin(lambda);
switch (mode) {
case "distance": {
//===== Calculating lengths of bigger circle
double x = s11 * s12 + c11 * c12 * cdelta;
double y = Math.sqrt(Math.pow(c12 * sdelta, 2) + Math.pow(c11 * s12 - s11 * c12 * cdelta, 2));
double ad = Math.atan2(y, x);
return ad * rad;
}
case "azimuth": {
double x = (c11 * s12) - (s11 * c12 * cdelta);
double y = sdelta * c12;
double z = Math.toDegrees(Math.atan(-y / x));
if (x < 0) z = z + 180;
double z2 = (z + 180) % 360 - 180;
z2 = Math.toRadians(-z2);
double anglerad2 = z2 - ((2 * pi) * Math.floor((z2 / (2 * pi))));
double anglerad = (anglerad2 * 180.) / pi;
anglerad = 360 - (anglerad - 90);
if (anglerad > 360) anglerad -= 360;
return anglerad;
}
default:
return 0;
}
}
coordinateAngleList：
private static double angleFromCoordinate(Double slat1, Double slong1, Double slat2, Double slong2) {
double long1 = slong1;
double long2 = slong2;
double lat1 = Math.toRadians(slat1);
double lat2 = Math.toRadians(slat2);
double dLon = Math.toRadians(long2 - long1);
double y = Math.sin(dLon) * Math.cos(lat2);
double x = Math.cos(lat1) * Math.sin(lat2) - Math.sin(lat1)
* Math.cos(lat2) * Math.cos(dLon);
return (Math.toDegrees(Math.atan2(y, x)) + 360) % 360;
}
pixelSizeList：
private static double calculatePixelSize(double altitude, double FOV, double imgWidth, double imgHeight) {
double halfFOV = FOV / 2;
double angleA = 180 - 90 - halfFOV;
double hypotenuse = altitude / Math.sin(angleA);
double imageDiagonalInMeters = Math.sqrt(Math.pow(hypotenuse, 2) - Math.pow(altitude, 2));
double imageDiagonalInPixels = Math.sqrt(Math.pow(imgWidth, 2) + Math.pow(imgHeight, 2));
return imageDiagonalInMeters / imageDiagonalInPixels;
}
以下是每个列表的前10个值：
Distance: [48.46373238266117, 48.71355037065455, 49.85503769989944, 48.52930211808859, 48.510404299271855, 48.94825023128212, 48.19766435644759, 49.451021971786204, 48.85744749197166, 50.080448602974066]
Azimuth: [230.16731156516713, 222.50205323598703, 231.0321217131937, 225.42496727180497, 225.3540760894774, 237.94887148656915, 300.046347389977, 15.525254536580519, 50.593577501672826, 56.856166424208084]
Coordinate Angel: [39.832235289576545, 47.497422524511194, 38.96742063247876, 44.57453556828523, 44.645426326236986, 32.050749366729804, 329.9540048495128, 254.47544091635925, 219.40687520849113, 213.14423324262788]
Pixel size: [0.060905719060422164, 0.0586466874395215, 0.05919405033739887, 0.05606758768342138, 0.061137652491726126, 0.06156441000532543, 0.061235064532873786, 0.05897139424334705, 0.06133247657402146, 0.06097993775843944]
之后，图像的简单旋转就会发生。我已经尝试使用我收到的角度和其他值来用Photoshop旋转图像，但几乎发生了同样的事情。这是旋转算法：
private void rotate(int numToRotate) {
//TODO correct rotation without cutting image
try {
for (int i = 0; i < numToRotate - 1; i++) {
BufferedImage image = ImageIO.read(new File("/Users/Nick/Downloads/geotagged-1/input" + i + "_1.png"));
// The required drawing location
int drawLocationX = 500;
int drawLocationY = 500;
// Rotation information
//double rotationRequired = azimuthList.get(i);
double rotationRequired = coordinateAngleList.get(i);
double locationX = image.getWidth() / 2;
double locationY = image.getHeight() / 2;
//AffineTransform tx = AffineTransform.getRotateInstance(Math.toRadians(rotationRequired), locationX, locationY);
//AffineTransformOp op = new AffineTransformOp(tx, AffineTransformOp.TYPE_BILINEAR);
AffineTransform transform = new AffineTransform();
transform.rotate(Math.toRadians(rotationRequired), locationX, locationY);
AffineTransformOp op = new AffineTransformOp(transform, AffineTransformOp.TYPE_BILINEAR);
// Drawing the rotated image at the required drawing locations
BufferedImage opImage = op.filter(image, null);
BufferedImage im = new BufferedImage((opImage.getWidth()), (opImage.getHeight()), BufferedImage.TYPE_INT_ARGB);
im.getGraphics().drawImage(opImage, drawLocationX, drawLocationY, null);
ImageIO.write(im, "png", new File("/Users/Nick/Dropbox/ЭЛСИ/ДЗЗ/AgroScan/rotated/" + i + ".png"));
}
} catch (IOException e) {
e.printStackTrace();
}
}
无论哪种方式，得到的图像都不会以稍微接近的直线结束。拼接基于创建一个大的BufferedImage并根据其中心之间的度量距离放置图像（对于之前计算的每个图像，pixelSize）。
旋转图像我做错了什么？我试过按方位角旋转，但这只会让它变得更糟。在我使用的任何算法中都有错误吗？