Blind restoration of aerial imagery degraded by spatially varying motion blur

This paper deals with deblurring of aerial imagery and develops a methodology for blind restoration of spatially varying blur induced by camera motion caused by instabilities of the moving platform. This is a topic of significant relevance with a potential impact on image analysis, characterization and exploitation. A sharp image is beneficial not only from the perspective of visual appeal but also because it forms the basis for applications such as moving object tracking, change detection, and robust feature extraction. In the presence of general camera motion, the apparent motion of scene points in the image will vary at different locations resulting in space-variant blurring. However, due to the large distances involved in aerial imaging, we show that the blurred image of the ground plane can be expressed as a weighted average of geometrically warped instances of the original focused but unknown image. The weight corresponding to each warp denotes the fraction of the total exposure duration the camera spent in that pose. Given a single motion blurred aerial observation, we propose a scheme to estimate the original focused image affected by arbitrarily-shaped blur kernels. The latent image and its associated warps are estimated by optimizing suitably derived cost functions with judiciously chosen priors within an alternating minimization framework. Several results are given on the challenging VIRAT aerial dataset for validation. © 2014 SPIE.