Inter-Camera Color Correction for Multispectral Imaging with Camera Arrays Using a Consensus Image

This paper introduces a novel method for inter-camera color calibration for multispectral imaging with camera arrays using a consensus image. Capturing images using multispectral camera arrays has gained importance in medical, agricultural, and environmental processes. Due to fabrication differences, noise, or device altering, varying pixel sensitivities occur, influencing classification processes. Therefore, color calibration between the cameras is necessary. In existing methods, one of the camera images is chosen and considered as a reference, ignoring the color information of all other recordings. Our new approach does not just take one image as reference, but uses statistical information such as the location parameter to generate a consensus image as basis for calibration. This way, we managed to improve the PSNR values for the linear regression color correction algorithm by 1.15 dB and the improved color difference (iCID) values by 2.81.