Minimal hitting set (MHS) problem is an important problem with widely applications in artificial intelligence. During computing all minimal hitting set, how to check the minimality of hitting sets is a key issue. Most of exhaustive MHS algorithms ensure the minimality of results by using subset checking method where its effectiveness is mainly relevant to the scale of minimal hitting sets, i.e., the larger the scale of the MHSs is, the lower the effectiveness of this method has. Consequently, when coming to solve the massive cases, the effectiveness of these algorithms is not high. To overcome this problem, this paper proposes independent coverage checking (ICC) and then develops it into an incremental method named ⅡCC. The effectiveness of this method is irrelevant to the scale of minimal hitting sets. Moreover, when computing all MHS by the incremental MHS algorithm with ⅡCC, it can incrementally test the minimality of candidate solutions, resulting in cutting down many unnecessary non-minimal hitting sets. ⅡCC is used to optimize the Boolean algorithm which is an incremental MHS algorithm using subset checking. The results show that ⅡCC method significantly outperforms the subset checking methods in terms of running time.