In this paper

the importance of cost aggregation

also called similarity measure

for belief propagation and the interaction of them are discussed.A global stereo matching algorithm is proposed by combining the belief propagation and local edge construction-based cost aggregation.First

a virtual closed edge is formed surrounding each pixel via second derivative operator in order to construct an adaptive window for the centered pixel.Then

the local cost aggregation is calculated on support pixels in an adaptive window.Finally

accelerated belief propagation optimization algorithm is used to obtain the disparity.The experiments based on the Middlebury benchmark indicate that the local edge construction-based cost aggregation can do well with belief propagation optimization and show encouraging results of the proposed stereo matching algorithm.