Joint de-noising and fusion of 2D video and depth map sequences sensed by low-powered tof range sensor
We propose a joint de-noising and data fusion approach where the fused modalities come from conventional high-resolution photo or video camera and low-resolution range sensor of Time-of-flight (ToF) type, operating in restricted conditions of low-emitting power and low number of sensor elements. Our approach includes identifying the various noise sources and suggesting suitable remedies at particular stages of data sensing and fusion. More specifically, fixed pattern noise and system noise are treated at a preliminary denoising stage working on range data only. In contrast to other 2D video/depth fusion approaches, which suggest working in planar coordinates, our approach includes additional denoising refinement in the space of 3D world coordinate system (i.e. point cloud space). Furthermore, the high-resolution grid resampling is performed as an iterative non-uniform to uniform resampling based on the Richardson method. This improves the performance compared to approaches based on low-to-high grid upsampling and subsequent refinement. We report experimental results where the achieved quality of fused data is the same as if the ToF sensor was operating in normal (low-noise) sensing mode.