IR Target detection is one of the key technologies in military applications. However, IR sensor has limitations of passive sensor such as low detection capability to weather and atmospheric effects. In recent years, sensor fusion is active research topic to overcome the limitations. Additional active SAR sensor is selected for sensor fusion because SAR sensor is robust to various weather conditions. The state-of-the-art detector, BMVT, has good performance in clear environment such as sky and sea background for small target. However, it shows poor performance when the target has extended size or the target is located in complex background such as ground-background with dense clutters. Therefore, we presents an improved ground target detection method based on the BMVT and Morphology filter (BMVT-M). The proposed algorithm consists of two parts: The first part is target enhancement based on the BMVT. The second part is clutter rejection and target enhancement based on the Morphology filter. In addition, conventional BMVT is not suitable to SAR image for target detection because SAR image has many shot noises. Therefore we apply a median filter before the BMVT in SAR image to suppress the shot noise. For the verification of the performance, experiments are performed in various cluttered backgrounds, such as ground, sea, and sky generated by the OKTAL-SE tool. The proposed algorithm showed upgraded detection performance than the BMVT in terms of detection rate and false alarm rate. Moreover, we discuss the applicability of the proposed method to the SAR and IR sensor fusion research.