Variables effecting photomosaic reconstruction and ortho-rectification from aerial survey datasets

TL;DR

This paper examines the factors affecting the quality of photomosaic reconstruction and ortho-rectification from aerial survey images, focusing on challenges and solutions in low-elevation imagery processing.

Contribution

It analyzes key variables influencing image stitching and structure from motion techniques for ortho-rectification in Irish aerial survey projects.

Findings

Identifies issues like insufficient keypoints and parallax in low-elevation imagery.

Proposes solutions to improve image stitching and ortho-rectification.

Demonstrates applications in urban and rural Irish projects.

Abstract

Unmanned aerial vehicles now make it possible to obtain high quality aerial imagery at a low cost, but processing those images into a single, useful entity is neither simple nor seamless. Specifically, there are factors that must be addressed when merging multiple images into a single coherent one. While ortho-rectification can be done, it tends to be expensive and time consuming. Image stitching offers a more economical, low-tech approach. However direct application tends to fail for low-elevation imagery due to one or more factors including insufficient keypoints, parallax issues, and homogeneity of the surveyed area. This paper discusses these problems and possible solutions when using techniques such as image stitching and structure from motion for generating ortho-rectified imagery. These are presented in terms of actual Irish projects including the Boland's Mills building in Dublin's city centre, the Kilmoon Cross Farm, and the Richview buildings on the University College Dublin campus. Implications for various Irish industries are explained in terms of both urban and rural projects.