Aiming at infrared dim and small targets detection in complex background,a new kernel norm estimation method was proposed based on the non-convex tensor low-rank approximation algorithm with asymmetric spatial-temporal total variation regularization,replacing the original estimation method in the algorithm.An adaptive weight tensor based on structure tensor and multi-structure element Top-Hat filtering was proposed to constrain the target tensor,which had enhanced the sparsity and suppressed the remaining strong edge structures of the target tensor.Experimental results show that the proposed improved algorithm can better eliminate the influence of strong edge structure on the detection results,and has a lower false alarm rate than the original algorithm under the condition of ensuring the detection rate.
关键词
红外小目标检测/张量恢复/张量核范数/多结构元Top-Hat滤波
Key words
infrared small target detection/tensor recovery/tensor nuclear norm/multi-structure element Top-Hat filtering
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