Abstract
The miniaturization of hyperspectral cameras has opened a new path to capture spectral information. One such camera, called the hybrid linescan camera, requires accurate control of its movement. Contrary to classical linescan cameras, where one line is available for every band in one shot, the latter asks for multiple shots to fill a line with multiple bands. Unfortunately, the reconstruction is corrupted by a parallax effect, which affects each band differently. In this article, we propose a two-step procedure, which first reconstructs an approximate datacube in two different ways, and second, performs a corrective warping on each band based on a multiple homography framework. The second step combines different stitching methods to perform this reconstruction. A complete synthetic and experimental comparison is performed by using geometric indicators of reference points. It appears throughout the course of our experimentation that misalignment is significantly reduced but remains non-negligible at the potato leaf scale.
Highlights
Near in situ agriculture observation has experienced a massive boom in recent years with the arrival of the big data era
Among hyperspectral imaging (HSI) compact sensors—which may be carried by unmanned aircraft vehicles (UAV)—only multishot [10] ones can yield images with a large spatial spectral and time resolution
To reconstruct a sub-datacube in each zone, the first step is based upon finding a frame step number shift, which derives from a spatial drift between manually extracted feature points from raw images
Summary
Near in situ agriculture observation has experienced a massive boom in recent years with the arrival of the big data era. Among HSI compact sensors—which may be carried by UAVs—only multishot (spatiospectral linescan) [10] ones can yield images with a large spatial spectral and time resolution. This fine resolution enables to obtain accurate radiance images of parts of vegetation crops. The angle of view—which is different from the ground reflected vertical ray, called NADIR—of different spectral bands associated with various vegetation leaf heights leads to non-rigid object movements in the scene This effect cannot be neglected at the pixel scale, and corrective steps such as orthorectification are needed to narrow this geometric effect by referring, for example, to image stitching methods
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