Hyperspectral imaging is a key technology for monitoring agricultural crops and vegetation. It can be used for health estimation and the early detection of disease symptoms in plants. This can help to reduce the use of pesticides by allowing targeted and early intervention. Cost-efficient hyperspectral imaging systems are necessary to meet the increasing demand for monitoring techniques for agricultural products. These systems usually suffer from sub-optimal image quality. Here we present a digital aberration correction for hyperspectral image data.
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