Infrared small target detection based on bilateral filtering algorithm with similarity judgments

Abstract

Infrared small target detection is part of the key technologies in infrared precision-guided, search and track system.Resulting from the relative distance of the infrared image system and the target is far, the target becomes small, faint and obscure. Furthermore, the interference of background clutter and system noise is intense. To solve the problem of infrared small target detection in a complex background, this paper proposes a bilateral filtering algorithm based on similarity judgments for infrared image background prediction. The algorithm introduces gradient factor and similarity judgment factor into traditional bilateral filtering. The two factors can enhance the accuracy of the algorithm for smooth region. At the same time, spatial proximity coefficients and gray similarity coefficient in the bilateral filtering are all expressed by the first two of McLaughlin expansion, which aiming at reducing the time overhead. Simulation results show that the proposed algorithm can effectively suppress complex background clutter in the infrared image and enhance target signal compared with the improved bilateral filtering algorithm, and it also can improve the signal to noise ratio (SNR) and contrast. Besides, this algorithm can reduce the computation time. In a word, this algorithm has a good background rejection performance.

Infrared Small Target Detection Based on Singularity Analysis and Constrained Random Walker

“…Conventional methods can be divided into four categories: filter-based methods [8][9][10], data structure-based methods [11][12][13][14], human vision system-based methods (HVS) [1,[15][16][17][18][19] and progressive detection-based methods [3-5, 7, 20]. a) Filter-based methods: Filtering-based techniques have been frequently utilized in small target detection based on the differences in the spatial organization and gray information between the target and background.…”

“…a) Filter-based methods: Filtering-based techniques have been frequently utilized in small target detection based on the differences in the spatial organization and gray information between the target and background. Based on a similarity judgment, a bilateral filtering algorithm [8] was proposed to judge the image boundary accurately. However, the texture residual of the background led to a high false alarm rate when the signal-to-noise ratio was low.…”