Scan line optimization for Tri stereo planetary images
In this paper, we propose a new scan line optimization method for matching the triplet of images. In the present paper, the triplets are initially matched using an area based local method. The cost is stored in a structure called as the Disparity Space Image (DSI). Using the global minimum of this cost the initial disparity is generated. Next the local minima are considered as potential matches where global minimum gives erroneous results. These local minima are used for optimization of disparity. As the method is a scanned line optimization, it use popularly resampled images. The experiment is performed using Terrain Mapping Camera images from the Chandrayaan-1 mission. In order to validate the result for accuracy, Lunar Orbiter Laser Altimeter dataset from Lunar Reconnaissance Orbiter mission is used. The method is again verified using standard Middlebury stereo dataset with ground truth. From experiments, it has been observed that using optimization technique for triplets, the total number of correct matches has increased by 5–10 % in comparison to direct methods. The method particularly gives good results at smooth regions, where dynamic programming and blockmatching gives limited accuracy.