Synthetic Aperture Radar (SAR) is the most widely used sensor for ship detection from space but optical sensors are increasingly used in addition of these. The combined use of these sensors in an operational framework becomes a major stake of the efficiency of the current systems. It becomes also a source of the increased complexity of these systems. Optical and SAR signals of a maritime scene have many similarities. These similarities allow us to define a common detection approach presented in this paper. Beyond the definition of a single algorithm for both types of data, this study aims to define an algorithm for the detection of vessels of any size in any resolution images. After studying the signatures of vessels, this second goal leads us to define a detection strategy based on multi-scale processes. It has been implemented in a processing chain into two major steps: first targets that are potentially vessels are identified using a Discrete Wavelet Transform (DWT) and Constant False Alarm Rate (CFAR) detector. Second among these targets, false alarms are rejected using a multi-scale reasoning on the contours of the targets. The definition of this processing chain is made with respect to three constraints: the detection rate should be 100%, the false alarm rate should be as low as possible and finally the processing time must be compatible with operations at sea. The method was developed and tested on the basis of a very large data set containing real images and associated detections. The obtained results validate this approach but with limitations mainly related to the sea state.