A Height Andtexture Information Intergrated Approch for Object Extraction Applied to Automatic Aerial Triangulation

This paper proposes a method of objects extraction based high and color texture features. Trees or forests are interested objects in this paper, which are higher than their surroundings. According to the disparity image processed, at first, the original color aerial images are segmented into the high and low objects, next, on the basis of preliminary results, the trees are refined by Fuzzy C-Mean with the texture and color features from the high and low areas. With above results, in this paper, an architecture is presented that observed points on forest and on non-forest are divided into two different groups in automatic aerial triangulation. This is because the matching accuracy and reliability of observed points on trees is lower than on non-trees. To decrease the negative influence of the observed points on trees, the observed points in two different groups are given the different a’priori standard deviation of photo coordination measurement and weights. The experiment results have proved that the method of observed points grouped can improve the accuracy of automatic aerial triangulation in forest-covered regions..