We propose improved multilevel filters （IMLFs） involving the absolute value operation into the algorithmic framework of traditional multilevel filters （MLFs） to improve the robustness of infrared small target enhancement techniques under a complex infrared cluttered background. Compared with the widely used small target enhancement methods which only deal with bright targets, the proposed technique can enhance the infrared small target, whether it is bright or dark. Experimental results verify that the proposed technique is efficient and practical.
A novel indirect building localization technique based on a prominent solid landmark from a forward- looking infrared imagery is proposed to localize low, deeply buried, or carefully camouflaged buildings in dense urban areas. First, the widely used effective methods are applied to detect and localize the solid landmark. The building target is then precisely indirectly localized by perspective transformation according to the imaging parameters and the space constraint relations between the building target and the solid landmark. Experimental results demonstrate this technique can indirectly localize buildings in dense urban areas effectively.
