RB-Dust -- A Reference-based Dataset for Vision-based Dust Removal
This dataset addresses a specific problem for researchers and developers working on vision-based systems for autonomous agricultural machines, but it is incremental as it fills a niche gap without introducing new methods.
The authors tackled the lack of datasets for validating dust removal algorithms in agricultural settings by creating the RB-Dust dataset, which includes dusty and dust-free images captured under controlled conditions, and validated it using contrast enhancement and dehazing algorithms, showing its applicability for tasks like person classification.
Dust in the agricultural landscape is a significant challenge and influences, for example, the environmental perception of autonomous agricultural machines. Image enhancement algorithms can be used to reduce dust. However, these require dusty and dust-free images of the same environment for validation. In fact, to date, there is no dataset that we are aware of that addresses this issue. Therefore, we present the agriscapes RB-Dust dataset, which is named after its purpose of reference-based dust removal. It is not possible to take pictures from the cabin during tillage, as this would cause shifts in the images. Because of this, we built a setup from which it is possible to take images from a stationary position close to the passing tractor. The test setup was based on a half-sided gate through which the tractor could drive. The field tests were carried out on a farm in Bavaria, Germany, during tillage. During the field tests, other parameters such as soil moisture and wind speed were controlled, as these significantly affect dust development. We validated our dataset with contrast enhancement and image dehazing algorithms and analyzed the generalizability from recordings from the moving tractor. Finally, we demonstrate the application of dust removal based on a high-level vision task, such as person classification. Our empirical study confirms the validity of RB-Dust for vision-based dust removal in agriculture.