Moving weak point target detection and estimation with three-dimensional double directional filter in IR cluttered background

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Abstract
We assess the performance of a novel three-dimensional double directional filtering (3DDDF) algorithm for detecting and tracking weak moving dim targets against a complex cluttered background in infrared (IR) image sequences. This proposed method increases the target energy accumulation ability further than the three-dimensional directional filter (3DDF) method. Prior to the filtering, a new prewhitening method termed a three-dimensional spatialtemporal adaptive prediction filter (TDSTAPF) is used to suppress the cluttered background. Extensive experiment results demonstrate the proposed algorithms' ability to detect weak dim point targets against a complex cloud-cluttered background in real IR image sequence and the performance comparisons of the proposed method and 3DDF.

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