Assorted Pixels: Multi-sampled Imaging with Structural Models

Abstract. Multi-sampled imaging is a general framework for using pixels on an image detector to simultaneously sample multiple dimensions of imaging (space, time, spectrum, brightness, polarization, etc.). The mosaic of red, green and blue spectral filters found in most solid-state color cameras is one example of multi-sampled imaging. We briefly describe how multi-sampling can be used to explore other dimensions of imaging. Once such an image is captured, smooth reconstructions along the individual dimensions can be obtained using standard interpolation algorithms. Typically, this results in a substantial reduction of resolution (and hence image quality). One can extract significantly greater resolution in each dimension by noting that the light fields associated with real scenes have enormous redundancies within them, causing different dimensions to be highly correlated. Hence, multi-sampled images can be better interpolated using local structural models that are learned offline from...

• Type: Conference
• Year: 2002
• Where: ECCV
• Authors: Shree K. Nayar, Srinivasa G. Narasimhan
• Keywords: Color Filters, Computer Vision, Dynamic Range Color, ECCV 2002, Multi-sampled Imaging, Multiple Dimensions, Solid-state Color Cameras