A shadow-removal based saliency map for point feature detection of underwater objects

Liqin Fu, Yiru Wang, Zhebin Zhang, Rui Nian, T. Yan, A. Lendasse
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引用次数: 5

Abstract

The point feature detection is one of the most essential and fundamental tasks for underwater objects in ocean investigations. In this paper, a streamline AUV system that adopts the side scan sonar on board has been set up to explore our underwater visual tasks. Before attempting to detect the point features, the raw underwater sonar images must be preprocessed by shadow removal. The saliency map will be further explored with the contrast determination filter at various scales and then the point feature detection model can be completed on the basis of the saliency map. It is shown from the simulation experiments that the proposed model could achieve great performances in the point feature detection with both robustness and effectiveness.
一种基于去阴影的水下目标点特征检测显著性图
点特征检测是海洋水下目标探测中最重要、最基础的任务之一。本文建立了一种采用侧扫声纳的流线型水下航行器系统,用于探索我们的水下视觉任务。在试图检测点特征之前,必须对原始水下声纳图像进行去影预处理。利用对比度确定滤波器在不同尺度下对显著性图进行进一步探索,然后在显著性图的基础上完成点特征检测模型。仿真实验表明,该模型在点特征检测方面具有较好的鲁棒性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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