Errors processing large images with SIFT OpenCV
I would split the image into smaller windows. So long as you know the windows overlap (I assume you have an idea of the lateral shift) the match in any window will be valid.
You can even use this as a check, the translation between feature points in any part of the image must be the same for the transform to be valid
I want to use OpenCV Python to do SIFT feature detection on remote sensing images. These images are high resolution and can be thousands of pixels wide (7000 x 6000 or bigger). I am having trouble with insufficient memory, however. As a reference point, I ran the same 7000 x 6000 image in Matlab (using VLFEAT) without memory error, although larger images could be problematic. Does anyone have suggestions for processing this kind of data set using OpenCV SIFT?
OpenCV Error: Insufficient memory (Failed to allocate 672000000 bytes) in cv::OutOfMemoryError, file C:\projects\opencv-python\opencv\modules\core\src\alloc.cpp, line 55
OpenCV Error: Assertion failed (u != 0) in cv::Mat::create, file 
(I'm using Python 2.7 and OpenCV 3.4 in the Spyder IDE on a Windows 64-bit with 32 GB of RAM.)