Image inpainting strategy for Kinect depth maps

Huimin Yao, Yan Chen, Chenyang Ge · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013

The great advantage of Microsoft Kinect makes the depth acquisition real-time and inexpensive. But the depth maps directly obtained with the Microsoft Kinect device have absent regions and holes caused by optical factors. The noisy depth maps affect lots of complex tasks in computer vision. In order to improve the quality of the depth maps, this paper presents an efficient image inpainting strategy which is based on watershed segmentation and region merging framework of the corresponding color images. The primitive regions produced by watershed transform are merged into lager regions according to color similarity and edge among regions. Finally, mean filter operator to the adjacent pixels is used to fill up missing depth values and deblocking filter is applied for smoothing depth maps.

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