Unexploded ordnance (UXO) survey is the foremost task of clearance project. Transient electromagnetic method (TEM) is proved effective for UXO survey. However, it is still difficult for TEM to detect small-size, ultra-shallow and dense UXO targets because the large-size devices and inversion methods for large-scale applications are usually ineffective. In the work, in order to avoid the complex inversion of apparent resistivity, the voltages acquired by our specified small-loop TEM system are used to depict a voltage distribution profile, which is then processed with an improved imaging algorithm. Several major influences on the secondary voltage image are discussed during UXO survey, including emitting coil size, target attitude, basin effect and shell thickness. Furthermore, an improved watershed imaging algorithm is proposed to obtain the best threshold marking and automatically realize the dense target discrimination. Oversegmentation resulting from burrs, noises, and scraps is reduced through background marking. And also under-segmentation is avoided during foreground marking through adaptive search of saddle point. The algorithm has been verified effective using simulation data and experiment data of UXO-like targets. INDEX TERMS Transient electromagnetic method, unexploded ordnance, image segmentation, watershed transform, adaptive saddle point search.