Distributed image steganography (DIS) (Y.S. Wu et al., 2004) is a new method of concealing secret information in several host images, leaving smaller traces than conventional steganographic techniques, and requiring a collection of affected images for secret information retrieval. Fusion system designs of the future will require enhanced security measures for distributed data communication. DIS, compared to other conventional steganographic techniques, can improve security and information hiding capacity because DIS leaves reduced signatures of hidden information in host images. The open literature does not offer effective detection methods and countermeasures for DIS, indicating that it can be potentially usable to criminals for unchallenged covert communication over the Internet and fusion architectures. In this paper, we explore a new information extraction method for both detecting and reversing DIS method by considering images as pseudo-random processes. The key idea is to estimate secret image as a random process, which is corrupted by a noise source (i.e. host image). The secret images may be nonlinear, non-Gaussian and non- stationary in nature, and can be disclosed by using some estimation techniques such as Kalman filtering. Our proposed method demonstrates great promise to reveal a secret image. Consequently, it is useful for intelligence gathering and information extraction in steganographic - images produced by DIS.