Recently, the field of infrared dim small target detection is paid considerable attention and various solutions are proposed. However, the problem of detection in complex background is unsolved. Clutter in complex backgrounds is difficult to eliminate, and significant results are difficult to obtain in target detection. For this reason, an improved algorithm, high-boost weighted tri-Layer local contrast measure (HB-WTLLCM) is proposed, which to enhance the target detection in complex background, and to improve the detection rate. An improved high boost filter was designed in this algorithm to preprocessed the original infrared image; then the tri-layer window was used for enhancing the local contrast. Finally, a weighted algorithm based on complexity evaluation was introduced for further target enhancement and random noise suppression. Experimental results show that, compared with mainstream algorithms, the proposed algorithm is stronger in target enhancement and improves detection rate under complex background of multiple buildings and trees. It is suggested that the HB-WTLLCM algorithm proposed in this paper can detect infrared dim and small targets well in complex background.