One of the main concerns in both desktop and pre-press environments is reliable color reproduction. This problem is addressed by the color management systems which are aiming at the production of so-called facsimile color. In order to use color management systems, one should know very well what the color space of the digital representation of the source image is. If this knowledge is not available, the CMS work-flows cannot be followed and more intelligent adaptive color correction techniques are required.Even if the source of the images and the scanning equipment is well-known, people often want to reproduce their originals “better”. In order to produce more appealing images, so-called color editing is required. This kind of editing includes range adjustments, tonal adjustments, saturation enhancement, global and selective color transformations etc. In order to increase productivity, these color corrections should be carried out automatically.The main goal of automatic color correction techniques thus consists of bringing the original images (the source of which might not be known) into a well-known calibrated RGB space such that the reproduction of the images is appealing to the viewer. In order to achieve these goals, the images have to be analyzed and reference points have to be detected.This paper is organized as follows. In the first section, we will introduce a general purpose model for automatic image correction. The general techniques exposed in that section will be illustrated by several case studies in the following sections. In the first case study, we will introduce an automatic tonal correction which has been used in the newspaper business for black and white images. The second case study will briefly describe adaptive techniques which have been used in order to convert negatives to a well-calibrated positive RGB space. The complexity of this technique is relatively low since it only involves a global color correction through the indication of a neutral point (which is equivalent to the specification of a global cast). In the third case study, we will deal with the general problem of automatic image correction of color images from unknown sources. In the last section, we will summarize the obtained results and indicate topics for future research.