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Open Access Guided Image Filtering based Disparity Range Control in Stereo Vision

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Generating a disparity map has been a challenging issue for several decades. To improve the quality of estimated disparity map and reduce the computational complexity, efficient cost matching functions and cost aggregation methods have been developed. Especially, in case of sequential stereo matching procedure, computational complexity causes a problem in terms of the real time processing. To overcome this problem, we propose a temporal domain stereo matching method using the guided image filtering. The advantage of temporal stereo matching method is restricting a disparity search range while calculating a matching cost value along the horizontal pixel line. Additionally, we adopt the guided image filtering to improve the quality of estimated disparity map in updating procedure. Since the guided image filtering aggregates the cost value by considering object boundary region, the result of stereo matching accuracy is improved than conventional temporal stereo matching method. From the experiment results, we check that the proposed method generates the most accurate disparity map than conventional method.

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Document Type: Research Article

Publication date: January 1, 2017

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