There is now growing concern regarding the safety of many prestressed concrete structures [1]. Of primary importance is the condition of the reinforcing steel, and much research effort has been expended on the development of non-destructive systems for assessing the integrity of internal reinforcing components [2–5]. Concrete is notoriously difficult to inspect, and most civil engineers, when assessing the quality of the internal reinforcing steel, will resort to a battery of tests, since a single test in isolation will rarely provide sufficient information. The system described below is a novel re-bar imaging system, based on an inductive principle, which should eliminate the need for many ancillary tests once fully developed [6]. A sensor which responds to the area and depth of metal in its sensing region is scanned across the concrete under inspection by a system linked to a computer. The signals acquired are stored, processed and displayed as grey level images. The initial images are blurred, due to the point spread function (PSF) of the sensor. These images have been significantly enhanced using a form of processing termed digital deconvolution. This form of processing allows considerable improvements in image quality to be realized from a single scan if the PSF of the sensor is known. In this instance, the PSF has been obtained through the development of an empirical model.