I know that DBSCAN requires two parameters (minPts and Eps). However, I am confused on what parameters are needed for OPTICS because some sources say it requires eps while others say it only requires minPts.
Which algorithm would be the better to use if I were trying to automatically determine the parameter values that would best discard outliers?
According to the original paper, both minPts and Eps are required. Those sources which say Eps is not required are probably using some method to automatically determine a good value for it. However, Eps is only included to reduce the runtime of the algorithm. It is not required.
Regarding which is best for outlier-removal, there's no better way than to support your decision with numbers: take a dataset and label its outliers, then run both algorithms against it. Use some sort of performance measurement for the clusters (AUC, F-score, etc.) to select the best.