An Efficient Storage of Infrared Video of Drone Inspections via Iterative Aerial Map Construction

In this letter, we present a novel compression algorithm of infrared video sequences captured during drone inspections based on iterative aerial map construction. In our approach, we first apply a stitching algorithm to construct a map of an inspected area assuming that a drone is flying at the same altitude by trajectory close to meander, so that each frame can have a partial overlap with other frame captured much earlier or later.

Then, we extract position and rotation angle within the map for each frame and use them as a side information for the video coding. In order to compress an input video sequence, we utilize a multi-view H.265/HEVC with two views. First view is a virtual view generated utilizing the decoded frames of the second view and the side information, whereas the input video is considered as the second view, which is encoded utilizing the virtual view as a reference for the inter-view prediction.

The proposed approach has two main benefits. First, the aerial map is generated during decoding utilizing the side information, i.e., the map is not embedded into a bit stream. Second, the inter-view prediction allows to exploit an additional redundancy, which is typical for a drone video. Experimental results show that the proposed algorithm provides 1.4%-2.4% bit rate savings comparing to H.265/HEVC.

The maximum possible bit rate savings are estimated from 15.5% to 18.9% assuming that the drone is repeatedly flying many times at exactly the same trajectory.