Target-less and targeted multi-camera color calibration

Sammanfattning: Multiple camera arrays are beginning to see more widespread use in a variety of different applications, be it for research purposes or for enhancing the view- ing experience in entertainment. However, when using multiple cameras the images produced are often not color consistent due to a variety of different rea- sons such as differences in lighting, chip-level differences e.t.c. To address this there exists a multitude of different color calibration algorithms. This paper ex- amines two different color calibration algorithms one targeted and one target- less. Both methods were implemented in Python using the libraries OpenCV, Matplotlib, and NumPy. Once the algorithms had been implemented, they were evaluated based on two metrics; color range homogeneity and color ac- curacy to target values. The targeted color calibration algorithm was more ef- fective improving the color accuracy to ground truth then the target-less color calibration algorithm, but the target-less algorithm deteriorated the color range homogeneity less than the targeted color calibration algorithm. After both methods where tested, an improvement of the targeted color calibration al- gorithm was attempted. The resulting images were then evaluated based on the same two criteria as before, the modified version of the targeted color cal- ibration algorithm performed better than the original targeted algorithm with respect to color range homogeneity while still maintaining a similar level of performance with respect to color accuracy to ground truth as before. Further- more, when the color range homogeneity of the modified targeted algorithm was compared with the color range homogeneity of the target-less algorithm. The performance of the modified targeted algorithm performed similarly to the target-less algorithm. Based on these results, it was concluded that the targeted color calibration was superior to the target-less algorithm.