从不同平面中选择最大值
我想从两个图像中获取最大值，同时保留其他信息。
例如，我有两个 HSL 格式的图像，我希望生成的图像由最亮的像素组成。 （这是一个例子，实际上我无法转换为RGB，找到最大值，然后转换回来）
所以我不能使用cvMax因为它会分别给我最大H，最大S和最大L 我需要的是任一
图像中具有最大 L 的图像，并附有同一图像中的 H 和 S 值（或其他信息）。
例如，考虑这些 2x1 像素图像及其 HSV 标量：
IplImage* img1 = cvCreateImage(cvSize(2, 1), IPL_DEPTH_32F, 3);
cvSet2D(img1, 0, 0, cvScalar(1, 2, 45)); // Remember: HSV values
cvSet2D(img1, 0, 1, cvScalar(3, 4, 123));
IplImage* img2 = cvCreateImage(cvSize(2, 1), IPL_DEPTH_32F, 3);
cvSet2D(img1, 0, 0, cvScalar(5, 6, 114));
cvSet2D(img1, 0, 1, cvScalar(7, 8, 33));
IplImage* result = cvCreateImage(cvSize(2, 1), IPL_DEPTH_32F, 3);
//Do something to get the brightest pixels
CvScalar px0 = cvGet2D(result, 0, 0);
CvScalar px1 = cvGet2D(result, 0, 1);
cout << px0.val[0] << " " << px0.val[1] << " " << px0.val[2] << endl;
cout << px1.val[0] << " " << px1.val[1] << " " << px1.val[2] << endl;
输出应该变为：
5 6 114
3 4 123
是否有一种简洁的“OpenCV”方法可以做到这一点，而不是制作我自己的（可能更慢的）算法来解析每个像素？
只是一个想法，但我可以做这样的事情吗？
- 将它们分割成6个灰度图像，（实际上，我已经有这种情况，所以我不需要分割）
- 取两个V图像，
- 生成每个元素的图（1U或8U图像），其中'0'或“1”值表示最高值分别位于第一张或第二张图像中。
- 使用此值组合来自其他平面的选定像素。
大胆的一步是我被困住的地方。
I want to get the maximum values from two images, while preserving other information.
For example, I have two images in HSL format, and I want the resulting image to consist of the brightest pixels. (this is an example, in reality I can't convert to RGB, finding max, and converting back)
So I cannot use cvMax because it will separately give me the maximum H, maximum S and maximum L.
What I need is an image with the maximum L from either image, accompanied by the H and S values (or other information) from the same image.
For example, consider these 2x1 pixel images, with their HSV scalars:
IplImage* img1 = cvCreateImage(cvSize(2, 1), IPL_DEPTH_32F, 3);
cvSet2D(img1, 0, 0, cvScalar(1, 2, 45)); // Remember: HSV values
cvSet2D(img1, 0, 1, cvScalar(3, 4, 123));
IplImage* img2 = cvCreateImage(cvSize(2, 1), IPL_DEPTH_32F, 3);
cvSet2D(img1, 0, 0, cvScalar(5, 6, 114));
cvSet2D(img1, 0, 1, cvScalar(7, 8, 33));
IplImage* result = cvCreateImage(cvSize(2, 1), IPL_DEPTH_32F, 3);
//Do something to get the brightest pixels
CvScalar px0 = cvGet2D(result, 0, 0);
CvScalar px1 = cvGet2D(result, 0, 1);
cout << px0.val[0] << " " << px0.val[1] << " " << px0.val[2] << endl;
cout << px1.val[0] << " " << px1.val[1] << " " << px1.val[2] << endl;
Output should become:
5 6 114
3 4 123
Is there a neat 'OpenCV' way of doing this, instead of making my own, possibly slower, algorithm that parses each pixel?
Just an idea, but can I do something like this?
- Split them into 6 grayscale images, (actually, I already have this situation, so I don't need to split)
- Take both V images,
- Generate a per-element map (1U or 8U image) where a '0' or '1' value means the highest value was in the first or second image respectively.
- Use this to combine selected pixels from the other planes.
The bold step is where I'm stuck.
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没有内置的 opencv 函数可以做到这一点，但编写自己的函数并不困难。
当然，可以
做一些小的优化，比如预先计算 j+w*i，或者使用指针访问而不是数组索引。
There is no build-in opencv function to do it, but it's not thah difficult to write your own.
You can simply
Of course, some little optimization can be done, like precalculating j+w*i, or using pointer access instead of array indexes.