Merge with extra: opencv/opencv_extra#827

BEBLID is a efficient binary descriptor learned with boosting. In several benchmarks it has proved to largely improve other binary descriptors like ORB or BRISK with the same efficiency. BEBLID describes using the difference of mean gray values in
different regions of the image around the KeyPoint, the descriptor is specifically optimized for
image matching and patch retrieval addressing the asymmetries of these problems.

This Pull Request ports the original code to OpenCV. The article explaining all the details and comparing the descriptor in several tasks can be found here.

Iago Suárez, Ghesn Sfeir, José M. Buenaposada, and Luis Baumela. BEBLID: Boosted efficient binary local image descriptor.
Pattern Recognition Letters, 133:366–372, 2020.

Testing this implementation with the code of the A-KAZE tutorial, we have found that, detecting 10000 keypoints with ORB and describing with BEBLID obtains 561 inliers (75%) whereas describing with ORB obtains only 493 inliers (63%).

Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

• I agree to contribute to the project under Apache 2 License.
• To the best of my knowledge, the proposed patch is not based on a code under GPL or other license that is incompatible with OpenCV
• The PR is proposed to proper branch
• There is reference to original bug report and related work
• There is accuracy test, performance test and test data in opencv_extra repository, if applicable
  Patch to opencv_extra has the same branch name.
• The feature is well documented and sample code can be built with the project CMake

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