Inferring the success parameter p of a binomial model from small samples affected by background

The problem of inferring the binomial parameter p from x successes obtained in n trials is reviewed and extended to take into account the presence of background, that can affect the data in two ways: a) fake successes are due to a background modeled as a Poisson process of known intensity; b) fake trials are due to a background modeled as a Poisson process of known intensity, each trial being characterized by a known success probability p_b.