Turbulence mitigation methods and their evaluation

Abstract

In general, long range detection, recognition and identification in visual and infrared imagery are hampered by turbulence caused by atmospheric conditions. The amount of turbulence is often indicated by the refractive-index structure parameter C n 2 . The value of this parameter and its variation is determined by the turbulence effects over the optical path. Especially along horizontal optical paths near the surface (land-to-land scenario) large values and fluctuations of C n 2 occur, resulting in an extremely blurred and shaky image sequence. Another important parameter is the isoplanatic angle, θ 0 , which is the angle where the turbulence is approximately constant. Over long horizontal paths the values of θ 0 are typically very small; much smaller than the field-of-view of the camera.Typical image artefacts that are caused by turbulence are blur, tilt and scintillation. These artefacts occur often locally in an image. Therefore turbulence corrections are required in each image patch of the size of the isoplanatic angle. Much research has been devoted to the field of turbulence mitigation. One of the main advantages of turbulence mitigation is that it enables visual recognition over larger distances by reducing the blur and motion in imagery. In many (military) scenarios this is of crucial importance. In this paper we give a brief overview of two software approaches to mitigate the visual artifacts caused by turbulence. These approaches are very diverse in complexity. It is shown that a more complex turbulence mitigation approach is needed to improve the imagery containing medium turbulence. The basic turbulence mitigation method is only capable of mitigating low turbulence.

Block matching and Wiener filtering approach to optical turbulence mitigation and its application to simulated and real imagery with quantitative error analysis

“…8,[15][16][17][18][19][20][21] Other related methods can also be found in the literature. [22][23][24][25][26][27][28] With most of these methods, a motion-compensated temporal average of video frames is computed first. The motion compensation, prior to temporal averaging, reduces the motion blurring that might otherwise be seen in LE imaging.…”

Turbulence mitigation methods for sea scenario imaging

“…In our standard turbulence mitigation method 6 -see Figure 1(a)-we first perform 'global motion compensation' (also known as registration) by estimating the alignment between subsequent image frames and compensating for the alignment differences. 7 After registration, we apply so-called dynamic super-resolution (DSR).…”