Meteosat image sequence coding in the Radon field

Abstract

The high demand for Meteosat image sequences for various fields and the high rate of presentation of methods dealing with these latter is facing with the low rate of presentation of remote sensing image sequence compression methods generally for different imagers. To tackle this issue, a novel Meteosat image sequence coding method in the Radon field is presented in this paper. The idea behind this paper is to show the contribution of the coding in Radon field to an efficient lossless compression. The Radon field, represented here by a new fast Mojette transform (FMT), gives a homogeneous field through a Mojette matrix engendered by the intra-projections and inter-projections redundancy. As a consequence, the use of an efficient block-based motion estimation (ME) algorithm such as adaptive rood pattern search (ARPS) becomes possible in a such environment, which can help to avoid many problems encountered when using the same techniques for remote sensing image as a block effect by way of example. In order to achieve a high lossless compression, the Sorted Run Length Coding (SRLC) is applied to encode besides the motion vectors (MVs), the residual error represented by separate long sequences of zeros in addition to other repeated symbols. The test phase showed that our proposed scheme exceeds the performances of the JPEG-LS standard. The proposed scheme can also be used as pre-technique for methods using Meteosat images in general and their sequences in particular after the decompression process such as meteorological phenomena tracking, segmentation, and so on.