Einav Namer

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Outdoor imaging is plagued by poor visibility conditions due to atmospheric scattering, particularly in haze. A major problem is spatially-varying reduction of contrast by stray radiance (airlight), which is scattered by the haze particles towards the camera. Recent computer vision methods have shown that images can be compensated for haze, and even yield a(More)
Recent studies have shown that major visibility degradation effects caused by haze can be corrected for by analyzing polarization-filtered images. The analysis is based on the fact that the path-radiance in the atmosphere (airlight) is often partially polarized. Thus, associating polarization with path-radiance enables its removal, as well as compensation(More)
Outdoor imaging in haze is plagued by poor visibility. A major problem is spatially-varying reduction of contrast by airlight, which is scattered by the haze particles towards the camera. However, images can be compensated for haze, and even yield a depth map of the scene. A key step in such scene recovery is subtraction of the airlight. In particular, this(More)
We present a nearly automatic graph-based segmentation method for patient specific modeling of the aortic arch and carotid arteries from CTA scans for interventional radiology simulation. The method starts with morphological-based segmentation of the aorta and the construction of a prior intensity probability distribution function for arteries. The carotid(More)
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