Infrared small target detection (IRSTD) task is vital in practical applications. It is still a challenge when the target size is very small and the local signal-to-noise ratio is particularly low. This paper proposed an Infrared Tall Patch-Matrix (ITPM) model, which takes a novel perspective to construct a lower-rank patch matrix structure to improve the detection performance of low-contrast small targets. Specifically, we use a sliding split window to reconstruct the original image into a suitable low-rank structure called Tall Patch-Matrix, which can increase the detection rate of low-contrast small targets and suppress most noise. Second, the High Local Variance Low-Rank and Sparse Decomposition (ITPM-HiLV-LRSD) method is used to perform low-rank and sparse decomposition of the Infrared Tall Patch-Matrix, and a Thin Singular Value Decomposition (Thin SVD) optimization strategy is proposed to further reduce the computational complexity. Given the absence of open literature datasets for detecting infrared targets in low-contrast small scenarios, we created a Low-contrast Small Target Detection Dataset (LSTDD) comprising 600 infrared target detection images with varied sky backgrounds. This dataset simulates low-contrast small targets across different signal-to-noise ratios. To demonstrate the generalizability of our method, we also conducted experiments on a representative low-contrast subset of real-world images from the SIRST dataset. Compared with six state-of-the-art methods, our proposed method excels in detecting low-contrast small targets with superior performance.
Building similarity graph...
Analyzing shared references across papers
Loading...
Yujia Liu
Wei Tang
Xuying Hao
Applied Sciences
Chinese Academy of Sciences
University of Chinese Academy of Sciences
Institute of Optics and Electronics, Chinese Academy of Sciences
Building similarity graph...
Analyzing shared references across papers
Loading...
Liu et al. (Thu,) studied this question.
www.synapsesocial.com/papers/699010df2ccff479cfe571f7 — DOI: https://doi.org/10.3390/app16041817
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: