High-Boost-Based Multiscale Local Contrast Measure for Infrared Small Target Detection

Robust and efficient infrared (IR) small target detection plays an important role in image processing for IR remote sensing. In order to detect the IR small target with high detection rate, low false alarm rate (FAR), and high detection speed, a novel method called high-boost-based multiscale local contrast measure (HB-MLCM) is proposed in this letter. First, improved high boost filter is proposed to enhance the high frequency signal where the target may appear and suppress the low frequency signal. Then, a simple MLCM is proposed for further enhancing the target and suppressing the background. Finally, a simple and adaptive thresholding method is used to segment targets from the contrast map. Experimental results on three real image sequences with various typical complex backgrounds demonstrate that the proposed method can effectively detect the target with faster speed, higher detection rate, and lower FAR compared with the state-of-the-art methods.