OpenCV MultiBandBlender doesn't work - opencv

Question

I try to blend my images into pano with MultiBandBlender, but it return black pano. But FeatherBlender works fine. What I doing wrong?
blendImages(const std::vector<cv::Point> &corners, std::vector<cv::Mat> images)
{
std::vector<cv::Size> sizes;
for(int i = 0; i < images.size(); i++)
sizes.push_back(images[i].size());
float blend_strength = 5;
cv::Size dst_sz = cv::detail::resultRoi(corners, sizes).size();
float blend_width = sqrt(static_cast<float>(dst_sz.area())) * blend_strength / 100.f;
cv::Ptr<cv::detail::Blender> blender = cv::detail::Blender::createDefault(cv::detail::Blender::MULTI_BAND);
//cv::detail::FeatherBlender* fb = dynamic_cast<cv::detail::FeatherBlender*>(blender.get());
//fb->setSharpness(1.f/blend_width);
cv::detail::MultiBandBlender* mb = dynamic_cast<cv::detail::MultiBandBlender*>(blender.get());
mb->setNumBands(static_cast<int>(ceil(log(blend_width)/log(2.)) - 1.));
blender->prepare(corners, sizes);
for(int i = 0; i < images.size(); i++)
{
cv::Mat image_s;
images[i].convertTo(image_s, CV_16SC3);
blender->feed(image_s, cv::Mat::ones(image_s.size(), CV_8UC1), corners[i]);
}
cv::Mat pano;
cv::Mat panoMask = cv::Mat::ones(dst_sz, CV_8UC1);
blender->blend(pano, panoMask);
return pano;
}

Answer 1

Three possible causes:
Try keeping all image_s and masks in a vector, and feed with the following structure:
for (int i = 0; i < images_s.size(); ++i)
blender->feed(images_s[i], masks[i], corners[i]);
Don't initialize panoMask to ones before blending.
Make sure corners are well defined

Answer 2

Actually, I can't compile your code with OpenCV 2.4, because of blender.get function. There is no such a function in my build of OpenCV 2.4.
Anyway, if you wish to make a panorama, you'd better not use resultRoi function. You need boundingRect. I suppose, it is really hard to get all horizontally aligned images for one panorama.
Also, look at my answer here. It demonstrates how to use MultiBandBlender.

Answer 3

Hey I was getting the same black pano while using MultiBand blender in opencv. Actually the issue was resolved by changing
cv::Mat::ones(image_s.size(), CV_8UC1)
to
cv::Mat::ones(image_s.size(), CV_8UC1)*255
This is because Mat::ones initialize all the pixels to a value of numerical 1, Thus, we need to muliply it with 255 in order to get a pure black & white mask.
And, thanks, your issue solved my problem :)