Direct and Global Component Separation from a Single Image Using Basis Representation

Previous research showed that the separation of direct and global components could be done with a single image by assuming neighboring scene points have similar direct and global components, but it normally leads to loss of spatial resolution of the results. To tackle such problem, we present a novel approach for separating direct and global components of a scene in full spatial resolution from a single captured image, which employs linear basis representation to approximate direct and global components. Due to the basis dependency of these two components, high frequency light pattern is utilized to modulate the frequency of direct components, which can effectively improve stability of linear model between direct and global components. The effectiveness of our approach is demonstrated on both simulated and real images captured by a standard off-the-shelf camera and a projector mounted in a coaxial system. Our results show better visual quality and less error compared with those obtained by the conventional single-shot approach on both still and moving objects.