Fig. 1. Diagram of proposed method

Fig. 2. Initial disparity maps based on different cost methods for Tsukuba. (a) Absolute difference in images gradients; (b) absolute difference in enhanced images gradients; (c) traditional Census transform; (d) Census transformation based on enhanced images gradients

Fig. 3. Schematic of adaptive window construction. (a) Cross-based support region construction; (b) adaptive window in Ref. [17]; (c) adaptive window in Ref. [14]; (d) adaptive window in proposed method

Fig. 4. Disparity maps under different illumination conditions for Aloe and Baby1. (a) Left image; (b) right image; (c) ground truth; (d) SAD+Grad; (e) AD+Cen; (f) AD+Grad+Cen; (g) proposed cost computation

Fig. 5. Disparity maps with different exposures for Aloe and Baby1. (a) Left image; (b) right image; (c) ground truth; (d) SAD+Grad; (e) AD+Cen; (f) AD+Grad+Cen; (g) proposed cost computation

Fig. 6. Disparity maps of different cost aggregation algorithms for textureless images. (a) Left images; (b) ground truth maps; (c) results of local stereo method based on guided filter; (d) error maps for method based on guided filter; (e) results of the proposed method; (f) error maps of the proposed method

Fig. 7. Experimental results on different parameter settings

Table 1. Experimental parameter settings

Table 2. Error matching rates of various cost computations under different illuminations%

Table 3. Error matching rates of various cost computations under different exposures%

Table 4. Error matching rates of various cost computations without radiometric changes%

Table 5. Error matching rates of different algorithms for different images%

Table 6. Error matching rates of different algorithms in all regions%

Table 7. Error matching rates of different algorithms for textureless images%

Table 8. Runtime comparison of different algorithms for benchmark stereo imagess