Old documents suffer from the passage of time: the paper is becoming more yellow, the ink is fading and the handling of these documents can still cause them to be damaged (e.g. stains may appear). The online edition of such documents can have profit of a cleaning step, the aim of which is to improve its readability. Some image filtering systems exist that require proper parameters to perform a cleaning. This article presents Georges, a CBR system designed to predict these parameters, for images of texts written in French, with several variants based on approximation, interpolation and extrapolation, based respectively of similarity, betweenness, and analogical proportion relations. The images are characterized by a dirtiness index, with the assumption that two images with similar dirtiness indexes would require similar sets of parameters for being cleaned. This index is based on the detection of the occurrences of a frequent French word on the pages and of averaging these occurrences. Human and automatic evaluations show that the proposed approach (with its variants) provides high-quality results.