access icon free Stereo matching using cost volume fusion for high dynamic range scenes

© The Institution of Engineering and Technology
Received 09/05/2017, Published 10/10/2017

A method is proposed to obtain accurate disparity maps for high dynamic range (HDR) scenes using stereo image pairs acquired under different exposure times and viewpoints. In HDR scenes, saturated pixels such as too-dark or too-bright pixels are inevitable because of the limited bit-depth representations of images. These saturated regions include little information for matching images and harm the performance of conventional stereo matching methods. To address this problem, a method is proposed that generates a new cost volume by fusing cost volumes obtained using different stereo image pairs taken under different exposure times as well as different points of view. In addition, the directional semi-global matching method is proposed to efficiently optimise the cost volume. Experimental results show that the proposed method generates more accurate results for saturated regions than existing methods on various datasets.

Inspec keywords: image representation; image resolution; optimisation; image fusion; stereo image processing; image matching

Other keywords: too-dark pixels; limited bit-depth image representation; HDR scenes; cost volume optimisation; stereo image pairs; stereo matching; too-bright pixels; exposure times; saturated regions; saturated pixels; cost volume fusion; disparity maps; high dynamic range scenes; directional semiglobal matching method

Subjects: Sensor fusion; Image recognition; Optimisation techniques; Computer vision and image processing techniques; Optimisation techniques

References

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