Material Imaging
A novel image deblurring dataset for materials science and light-optical microscopy. This dataset provides images with real out-of-focus and motion blur and a sharp reference image for each observation. The dataset includes image samples of lithium-ion batteries, Fe-Nd-B sintered magnets, 100Cr6 steel with a partially bainitic microstructure, and aluminium-silicon casting alloys. The dataset was acquired using a ZEISS AxioImager.Z2 Vario light microscope and the 6-megapixel camera Axiocam 506 color.
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Conventionally, the texture of the object is used for material imaging. However, this method can mistake an image of an object, for the object itself. This dataset furthers a new and more relevant method to classify the material of an object. This data is richer, compared to RGB images, because the time of flight responses correlate with the material property of an object. This makes the features, thus extracted, more suitable to infer the material information.
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This dataset has been taken using the Photonic Mixer Device (PMD) Selene Module. To capture the image, we have constructed a demonstrator setup consisting of five materials (i.e., foam board (location: center), crepe paper (location: top), polystyrene (location: right), bubble wrap (location: left), wax (location: bottom)). Each image has been taken at 5 different distances (uniformly distributed between 82 cm to 47 cm) and at 3 different orientations (uniformly distributed between -10 degree to 10 degree) for each material. To avoid noise, each image has been taken in dark environment.
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