关键词: 海底线检测, 侧窗快速引导滤波, PM滤波, Otsu算法, Canny算法

Abstract: [Purposes] Seabed line detection is crucial for side-scan sonar image processing.Addressing the issues of low automation and inefficiency in existing methods,this paper aims to achieve automated and accurate extraction of seabed lines. [Methods] The traditional Canny method is improved by introducing a side-window fast guided filtering and incorporating the Perona-Malik nonlinear diffusion equation to suppress speckle noise.The Otsu algorithm is employed to achieve adaptive selection of dual thresholds,and the gradual nature and symmetry constraints of seabed lines are utilized to repair fractured edges,completing the accurate extraction of seabed lines. [Findings] Experiments results show that,in scenes with suspended matter interference,the extraction accuracy of the proposed method increases from 34% to 54% for comparative methods to 98.71%,and the Euclidean distance decreases from 72 to 85 pixels to 5.313 pixels.In scenes without significant interference,the accuracy reaches 98.27%,and the Euclidean distance is 5.382 pixels,both outperforming other comparative methods. [Conclusions] This study provides an effective solution for automated seabed line extraction and significantly enhances the robustness of extraction in the presence of suspended matter interference.

Key words: seabed line detection, fast side window guided filtering, PM filtering, Otsu algorithm, Canny algorithm