Underwater image stitching is a technique employed to seamlessly merge images with overlapping regions, creating a coherent underwater panorama. In recent years, extensive research efforts have been devoted to advancing image stitching methodologies for both terrestrial and underwater applications. However, existing image stitching methods, which do not utilize detector information, heavily rely on matching feature pairs and tend to underperform in situations where underwater images contain regions with blurred feature textures. To address this challenge, we present an improved scale-invariant feature transform (SIFT) underwater image stitching method. This method enables the stitching of underwater images with arbitrarily acquired images featuring blurred feature contours and that do not require any detector information. Specifically, we perform a coarse feature extraction between the reference and training images, and then we acquire the target image and perform an accurate feature extraction between the reference and target images. In the final stage, we propose an improved fade-in and fade-out fusion method to obtain a panoramic underwater image. The experimental results show that our proposed method demonstrates enhanced robustness, particularly in scenarios where detecting feature points is challenging, when compared to traditional SIFT methods. Additionally, our method achieves higher matching accuracy and produces higher-quality results in the stitching of underwater images.

In this paper, a robust path-following control strategy is proposed to deal with the path-following problem of the underactuated autonomous underwater vehicle (AUV) with multiple uncertainties and input saturation, and the effectiveness of the proposed control strategy is verified by semi-physical simulation experiments. Firstly, the control laws are constructed based on the traditional backstepping method; the multiple uncertainties are treated as lumped uncertainties, which can be estimated and eliminated by the employed extended state observers (ESOs). In addition, the influence of input saturation can be compensated by the designed auxiliary dynamic compensators. Secondly, to simplify controller design and address the “complexity explosion”, two command filters are used to obtain the estimated value of the unknown sideslip angular velocity and the desired yaw angular acceleration, respectively. Finally, the superiority and robustness of the proposed control strategy are verified through computer simulation. A semi-physical simulation experiment platform is built based on the NI Compact cRIO-9068 and PLC S7-1200 to further demonstrate the effectiveness of the proposed control strategy.