<title>An adaptive model for restoration of optically distorted video frames</title>

Abstract

Atmospheric turbulence is a common problem in astronomy and long distance surveillance applications. It can lead to optical distortions that can significantly degrade the quality of the captured images and video. Quality improvement can be achieved through digital restoration methods that effectively suppress the effects of optical distortion. In this paper, atmospheric optical distortion is modeled as having two components: a dispersive component and a time-varying distortion component. A new restoration algorithm is introduced that compensates for dispersion using a fourth-order statistic and employs a new adaptive warping algorithm to suppress turbulent motion effects. The new algorithm is able to improve quality significantly and is able to handle difficult cases involving panning, zooming, and natural motion.

A Concatenated Model for Video Frame Interpolation

“…In next stage, the enlarged frames are compared against a reference frame. In particular, a dense motion vector field is computed [7,6,8] after which an adaptive warping algorithm is applied to warp the reference frame based on the dense motion vector field associated with each interpolated frame. In the last stage, the warped algorithm is compared with the interpolated image on a pixel-by-pixel basis.…”

A low bit-rate video coding approach using modified adaptive warping and long-term spatial memory

“…Augmenting the spatially decimated frames is an N -to-1 temporally decimated sequence of high spatial resolution reference frames (where N is large). A key aspect of the proposed coding scheme is an adaptive warping method 7,8 which is used to perform motion estimation and reconstruction at the receiver side. The approach is shown to yield improved subjective quality for sequences with low to moderate motion and high spatial detail.…”