Image-guided depth map upsampling using normalized cuts-based segmentation and smoothness priors
Suraj Krishnamurthy, Kalpathi Ramakrishnan · 2016
In this paper, we propose an image segmentation-based algorithm to perform upsampling of noisy low-resolution depth maps using information from the high-resolution color image. The depth map is initially upscaled using standard image interpolation technique, and then refined by a process based on the combination of Normalized Cuts segmentation and various smoothness priors in order to obtain a high quality highresolution depth map. Our method outperforms other existing methods when applied on both synthetic and real-world datasets.