Hyperspectral underwater target detection (HUTD) is a promising and challenging task in remote sensing image processing. Existing methods face significant challenges when adapting to nearshore environments, where cluttered backgrounds hinder the extraction of target signatures and exacerbate signal distortion. Hyperspectral unmixing (HU) demonstrates potential effectiveness for nearshore underwater target detection (UTD) by simultaneously extracting water background endmembers and separating target signals. To this end, this article investigates a novel nonlinear unmixing network for hyperspectral UTD, denoted as nonlinear unmixing network for hyperspectral-UTD (NUN-UTD), in which a well-designed autoencoder-based unmixing network is used to obtain the abundance map as the detection result. To address the weak underwater target signals, a target prior spectral preservation scheme is employed to guide the unmixing network in learning the accurate target abundance. Besides, to address the complexity of the nearshore environment, a pseudomixed data classification constraint is incorporated into the objective function to enhance the discriminative capability between the background and the target. Moreover, we adopt an additive postnonlinear model in the decoder to deal with the interactions between underwater spectra to account for the nonlinear effects between spectra of underwater substances. To validate the effectiveness of the proposed method, we constructed a hyperspectral dataset for nearshore UTD. Extensive experiments conducted on three real-world datasets and one simulated dataset demonstrate that our method achieves outstanding performance in HUTD.

中文翻译：

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使用高光谱非线性解混合自动编码器检测近岸水下目标


高光谱水下目标检测（HUTD）是遥感图像处理中一项有前景且具有挑战性的任务。现有方法在适应近岸环境时面临重大挑战，其中杂乱的背景阻碍了目标特征的提取并加剧了信号失真。高光谱分解 (HU) 通过同时提取水背景端元和分离目标信号，展示了近岸水下目标检测 (UTD) 的潜在有效性。为此，本文研究了一种新型的高光谱UTD非线性解混网络，称为高光谱UTD非线性解混网络（NUN-UTD），其中使用精心设计的基于自动编码器的解混网络来获得丰度图：检测结果。为了解决水下目标信号较弱的问题，采用目标先验光谱保存方案来指导解混网络学习准确的目标丰度。此外，为了解决近岸环境的复杂性，目标函数中加入了伪混合数据分类约束，以增强背景和目标之间的区分能力。此外，我们在解码器中采用加性后非线性模型来处理水下光谱之间的相互作用，以解释水下物质光谱之间的非线性效应。为了验证所提出方法的有效性，我们构建了近岸 UTD 的高光谱数据集。在三个真实数据集和一个模拟数据集上进行的大量实验表明，我们的方法在 HUTD 中取得了出色的性能。