Abstract
Stereo matching of two distanced cameras and structured-light RGB-D cameras are the two common ways to capture the depth map, which conveys the per-pixel depth information of the image. However, the results with mismatched and occluded pixels would not provide accurately well-matched depth and image information. The mismatched depth-image relations would degrade the performances of view syntheses seriously in modern-day three-dimension video applications. Therefore, how to effectively utilize the image and depth to enhance themselves becomes more and more important. In this paper, we propose an advanced multilateral filter (AMF), which refers spatial, range, depth, and credibility information to achieve their enhancements. The AMF enhancements could sharpen the image, suppress noisy depth, filling depth holes, and sharpen the depth edges simultaneously. Experimental results demonstrate that the proposed method provides a superior performance, especially around the object boundary.
Highlights
The three-dimensional (3D) video is widely recognized as a visual media technique which enables viewers to perceive the depth in a scene without special glasses
4 Experimental results To evaluate the effectiveness of advanced multilateral filter (AMF) and the rolling guidance refinement (RGR), the proposed depth enhancement system is experimented on Middlebury database [37, 38] and RGBD database
Virtual depth maps are generated by the stereo matching method on the Middlebury database, in addition, natural depth maps are produced by the stereo camera on the RGBD database
Summary
The three-dimensional (3D) video is widely recognized as a visual media technique which enables viewers to perceive the depth in a scene without special glasses. The DIBR technique synthesizes images at the desired viewpoint by using the color image and its corresponding depth map. It can be treated as an efficient data format for the 3D video. The source depth map could be generated by fast stereo matching technique with subsample stereo images or captured by RGB-D cameras with a lower resolution than the color image. The source depth map produced by fast stereo matching and depth camera usually has a lower resolution than the corresponding color image and contains a lot of noisy pixels including unknown pixels due to occlusions. The enhancements of the image and its depth become very important in 3D visualization
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