Atmospheric turbulence restoration by diffeomorphic image registration and blind deconvolution
This addresses image restoration for applications like surveillance or astronomy, but appears incremental as it builds on existing blocks.
The paper tackles the problem of restoring images degraded by atmospheric turbulence by introducing two new algorithms that combine blind deconvolution, elastic registration, and temporal filtering, and tests them on real desert images from the NATO RTG40 group.
A novel approach is presented in this paper to improve images which are altered by atmospheric turbulence. Two new algorithms are presented based on two combinations of a blind deconvolution block, an elastic registration block and a temporal filter block. The algorithms are tested on real images acquired in the desert in New Mexico by the NATO RTG40 group.