Generalized Mosaicing

Abstract

We present an approach that significantly enhances the capabilities of traditional image mosaicing. The key observation is that as a camera moves, it senses each scene point multiple times. We rigidly attach to the camera an optical filter with spatially varying properties, so that multiple measurements are obtained for each scene point under different optical settings. Fusing the data captured in the multiple images yields an image mosaic that includes additional information about the scene. This information can come in the form of extended dynamic range, high spectral quality, or enhancements to other dimensions of imaging. We refer to this approach as generalized mosaicing. The approach was tested using a filter with spatially varying transmittance and a standard 8-bit black/white video camera, to achieve image mosaicing with dynamic range comparable to imaging with a 16-bit camera. In another experiment, we attached a spatially varying spectral filter to the same camera to obtain mosaics that represent the spectral distribution (rather than the usual RGB measurements) of each scene point. We also discuss how generalized mosaicing can be used to explore other imaging dimensions.