Adaptive bilateral filtering for noise removal in depth upsampling

3D scene rendering requires depth maps and color information to produce high quality 3D results. Unfortunately, depth maps captured with the Time-of-flight (TOF) cameras have limited resolution and poor image quality, being severely influenced by the random and systematic noise, which makes them inapposite for generating high quality 3D images. In this paper, we have further analyzed a framework for upsampling the resolution of depth maps that jointly uses Gaussians of spatial and depth differences of low resolution depth map´s pixels along with Gaussian of color intensity difference from high resolution 2D color image of the same scene. The variance of the Gaussian functions controls the amount of smoothing in uni-planner area and sharpness at boundaries. Using bigger variance smooths uni-planner area but blurs edges and vice versa. We have devised a method to adaptively calculate and use variance to get smoother surface and sharper edges of upsampled depth map with minimized noise.