We develop a general theory of spatially-variant (SV) mathematical morphology for binary images in the euclidean space. The basic SV morphological operators (that is, SV erosion, SV dilation, SV opening, and SV closing) are defined. We demonstrate t
We present a simple and general framework for feature learning from point cloud. The key to the success of CNNs is the convolution operator that is capable of leveraging spatially-local correlation in data represented densely in grids (e.g. images).
Non-intrusive inspection systerms based on X-ray radiography techriques are rou tinely used at transport hubs to ensure the conforrmity of catgo content with the supplied shipping manifest. As trade volurmes increase and regulatiors become more strin
An optical vortex having an isolated point singularity is associated with the spatial structure of light waves. A polarization vortex (vector beam) with a polarization singularity has spatially variant polarizations. A phase vortex with phase singula
Vector beams with spatially variant polarization have attracted much attention in recent years, with potential applications in both classical optics and quantum optics. In this work, we study a polarization selection of spatial intensity distribution
