Infrared and Laser Engineering, Volume. 51, Issue 4, 20210417(2022)
Infrared small target detection based on dehazing enhancement and tensor recovery
Fig. 2. Infrared small target images. (a)-(c) Real scenes of sky background with thick cloud; (d)-(f) Real scenes of sky background with buildings and other complex occluders
Fig. 3. Construction of patch-tensor model (Left: Original infrared image; Right: Constructed patch-tensor)
Fig. 4. Nonlocal self-correlation property of unfolding matrices. (a) Infrared images; (b)-(d) Singular value curves of mode-1, mode-2, and mode-3 unfolding matrices
Fig. 5. Contrast results of dehazing enhancement in different scenes. (a) Seq.1; (b) Seq.2; (c) Seq.3; (4) Seq.4
Fig. 6. Detection results of proposed algorithm. (a) Original infrared images; (b) Input original images with global 3D surf plot; (c) Mark the detection result of the target with a rectangular box; (d) Local 3D surf plot of target
Fig. 7. Detection results of the different approaches to 4 sequences. (a) Original infrared images; (b) Top-Hat; (c) LoG; (d) LCM; (e) MPCM; (f) IPI; (g) PSTNN; (h) Proposed algorithm
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Yaping Wang, [in Chinese], Baohua Zhang. Infrared small target detection based on dehazing enhancement and tensor recovery[J]. Infrared and Laser Engineering, 2022, 51(4): 20210417
Category: Image processing
Received: Jun. 18, 2021
Accepted: Jan. 10, 2022
Published Online: May. 18, 2022
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