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High-precision detection of small targets with low signal-to-noise ratio in infrared (IR) images has great significance for IR precise guidance, video surveillance, etc. In this paper, we proposed a novel method called centre-surround high-boost filter-based improved local Weber contrast measure. First, centre-surround high-boost filter is proposed to fully utilize the grey difference information, which reduces the influence of the non-homogeneous background such as cumulus sky, sea-sky clutters and high brightness edge. Then, an improved local Weber contrast measure is used to construct the contrast operator of the ratio-difference joint form for further target contrast enhancement and arbitrary interference suppression. Finally, we apply an adaptive thresholding segmentation to find the true target. Experimental results on various cluttered background sequences demonstrate that our proposed method can detect small targets with higher detection rate and lower false alarm rate, and the performance is more stable than five comparable methods in diverse scenarios.

High-boost-based local Weber contrast method for infrared small target detection