  In this paper, we contrive a stereo matching algorithm with careful handling
of disparity, discontinuity and occlusion. This algorithm works a worldwide
matching stereo model which is based on minimization of energy. The global
energy comprises two terms, firstly the data term and secondly the smoothness
term. The data term is approximated by a color-weighted correlation, then
refined in obstruct and low-texture areas in many applications of hierarchical
loopy belief propagation algorithm. The results during the experiment are
evaluated on the Middlebury data sets, showing that out algorithm is the top
performer among all the algorithms listed there
