A Robust Disparity Map Estimation for Handling Outliers in Stereo Images

The paper focuses on estimating disparity map that can handle outliers. Outliers are the major challenging problem in stereo matching. The results obtained from depth maps are significantly affected by outliers regions that are present in the image. The stereo images are pre-processed using homomorphic filter. The Semi-global block matching method is used to estimate disparity information. Left to right consistency check method is applied to identify outliers. Outliers identified are classified as occlusion and mismatches and then they are refined. The proposed method is robust against illumination differences and recovers disparities at the object edges, occluded regions. The performance of the technique used is analyzed by percentage of bad matching pixel and root mean square error. Experimental results generated determine that the proposed algorithm gives more stable disparity maps.