Temporal interpolation in Meteosat images

The geostationary weather satellite Meteosat supplies us with a visual and an infrared image of the earth every 30 minutes. However, due to transmission errors some images may be missing. European TV weather reports are often supported by such infrared image sequences. The cloud movements in such animated films are perceived as being jerky due to the low temporal sampling rate in general and missing images in particular. In order to perform a satisfactory temporal interpolation we estimate and use the optical flow corresponding to every image in the sequence. The estimation of the optical flow is based on images sequences where the clouds are segmented from the land/water that might also be visible in the images. Because the pixel values measured correspond directly to temperature and because clouds (normally) are colder than land/water we use an estimated land temperature map to perform a threshold between clouds and land/water. The temperature maps are estimated using Rasmus Larsen et al. 2 observations from the image sequence itself at cloud free pixels and ground temperature measurements from a series of meteorological observation stations in Europe. The temporal interpolation of the images is based on a path of each pixel determined by the estimated optical flow. The performance of the algorithm is illustrated by the interpolation of a sequence of Meteosat infrared images.