In today's heterogeneous network environment, there is a growing demand for distrusted parties to jointly execute distributed algorithms on private data whose secrecy needed to be safeguarded. Protocols that support such kind of joint computation without complete sharing of information are called Secure Multiparty Computation (SMC) protocols. Applying SMC protocols in image processing is a challenging problem. Most of the existing SMC protocols are implemented based on cryptographic primitives like Oblivious Transfer that are too computational intensive for pixel-based operations. In this paper, we develop two efficient SMC protocols for distributed linear image filtering between two parties, one party with the original image and the other with the image filter. The first protocol is based on a combination of rank reduction and random permutation. The second one uses random perturbation with the help of a non-colluding third party. Experimental results show that both of them execute significantly faster than oblivious-transfer based techniques.