Analysis of moving DLT, image and seam selections algorithms with MS ICE, autostitch, and OpenCV stitcher for image stitching applications

The objective of image stitching is to merge several images into a single seamless mosaicked image. Image stitching finds its applications in numerous fields like image stabilization, medical imaging, satellite imaging etc. The results of the existing algorithms are unsatisfactory in specific images, where the images do not differ purely by rotation. Even, the processing time is excessive if there are numerous images with similar scenes or with many blurred images. This paper analyses two efficient image stitching algorithms, a) Moving Direct Linear Transformation (Moving DLT) and b) image and seam selections. In addition, we describe how each of these algorithms incorporate stitching multiple images to create big panoramas using techniques like bundle adjustment and stitching label estimation using particle filtering with partitioned sampling. The experimental results are compared with MS ICE, Autostitch, and OpenCV stitcher.