Parallelization of algorithms for image stitching using distributed memory architecture

The efficient use of satellite images for practical purposes depends upon the ability to combine them for the purposes of analysis. However, this process involves many computationally intensive computer vision algorithms. Assembling large images usually requires costly hardware with a large amount of memory. This paper addresses this problem by proposing a system that implements algorithms required in the process of image stitching, viz. algorithms for feature detection, feature description, feature matching, image transformation and image compositing, in parallel on a distributed memory architecture. The proposed system aims to improve the performance of the image stitching process while providing a more easily scalable system.