Correction of images from a panoramic-view camera system in the case of rain, incident light and contamination

Abstract

The invention relates to correcting input image data, from a plurality of cameras of a vehicle panoramic-view system. includes: capturing input image data by the cameras, which are negatively influenced by rain, incident light and/or dirt, and providing to a trained artificial neural network, converting, by the trained network, the input image data into corrected output image data without negative influence, determining a certainty measure which is dependent on the degree of wetting by water, incident light and/or contamination for an image of the input image data, and characterizing the certainty of the trained network that the image correction of the network is accurate, and outputting, by the trained network, the output image data and the determined certainty measure. The method advantageously allows object recognition when cameras are fogged up and generation of an image data stream for human and computer vision from a network for an optimized correspondence search.