This paper proposes a stereo vision cooperative algorithm for high quality dense disparity mapping. This algorithm iteratively performs the local adaptive aggregation and inhibitive magnification based on the morphologic similarity with adaptive weight, and generates high quality dense disparity map effectively. This paper also extends the cooperative algorithm to trinocular stereo vision system. By rebuilding the camera coordinate system, the trinocular images are rectified, and the support area and trinocular inhibition area are established in disparity space based on the continuity and uniqueness constrains. Experimental results show that the trinocular stereo vision cooperative algorithm can generate accurate real dense disparity maps, and the occlusions in multiple baseline directions can also be detected. This algorithm is especially suitable for stereo vision system with multiple cheap camera to realize high quality dense disparity mapping without more hardware and software.