The electro-optic infra-red (EO/IR) camera systems of unmanned aerial vehicles (UAV) are equipped with an infra-red sensor to detect targets even in low visibility environments. However, the infra-red sensor is easily affected by diverse noises, and it is essentially needed to process a contrast expansion using the histogram equalization because of low output level of the sensor. But the classical histogram equalization (HE) for IR image processing has side effects such as lack of contrast expansion and saturation phenomenon. In addition, the local area processing (LAP) for saturation reduction has been studied, but LAP shows low performance to reduce saturation and non-uniformities between divided areas. In this study, we propose the interlaced HE (IHE) method in order to solve the problems about the saturation and the non-uniformities. Compared with the conventional HE method, the proposed method maintains the same performance of image contrast expansion with the 6.72 entropy, and the saturation was dramatically reduced as its variance was reduced from 82[%] to 77[%].