In this paper, we propose a multi-sensor super-resolution framework for hybrid imaging to super-resolve

data one modality by taking advantage of additional guidance images of a complementary modality.

This concept is applied to hybrid 3-D range imaging in image-guided surgery, where high-quality photomet-

ric data is exploited to enhance range images of low spatial resolution. We formulate super-resolution based

on the maximum a-posteriori (MAP) principle a-In this paper, we propose a multi-sensor super-resolution framework for hybrid imaging to super-resolve

data　one modality by taking advantage of additional guidance images of a complementary modality.

This concept is applied to hybrid 3-D range imaging in image-guided surgery, where high-quality photomet-

ric data is exploited to enhance range images of low spatial resolution. We formulate super-resolution based

on the maximum a-posteriori (MAP) principle a