The geo-referencing information of the satellite imagery is obtained by the use of either attitudes and velocity/position provided by the satellite instrumentation , nevertheless the positioning using this approach depend directly on the quality of the ephemeris data. The image-to-image registration aims to find a geometric transformation relating two or more images in order to locate them in the same geographic reference. As the first Algerian high-resolution satellite ALSAT- 2A, has a nominal positional accuracy of around 300m, this last approach can be used to estimate and improve the raw image positional quality where these images are registered to orthoimages that are more accurate. Therefore, the resulting image have an enhanced geolocation quality than the one calculated using the estimation of the line of sight model. The purpose of this work is to provide a framework to automatically estimate the positional quality of Alsat2A image for cataloguing purpose, also to improve the geolocation accuracy of the level 1-A (geometrically raw) images by using other imagery that is already geo-localized with better accuracy. Landsat 8 orthoimagery coverage represents a data source that is worldwide available and its accuracy is sufficient for our work. Therefore, it is used as reference images to estimate and enhance the quality of raw ALSAT-2A images. This work is based on the use of open-source software such python, OpenCv and PostgreSQL and the open-data e.g. geo-referenced quick looks of landsat8 provided by EarthExplorer. Many experimentations has been conducted to decide on which algorithm is better to enhance the contrast and which spectral channel to use, also many methods for the homologue points extraction and description have been evaluated. Then, points of interest extracted from the reference orthoimagery are fed into a geographic database, allowing the use of these points as known ground points to estimate and enhance the quality of Alsat-2A imagery.