水下
计算机科学
计算机视觉
人工智能
利用
信号(编程语言)
视皮层
相关性(法律)
噪音(视频)
感知
图像(数学)
地质学
神经科学
海洋学
计算机安全
政治学
法学
生物
程序设计语言
作者
Marco Reggiannini,Davide Moroni
出处
期刊:Remote Sensing
[Multidisciplinary Digital Publishing Institute]
日期:2020-12-23
卷期号:13 (1): 22-22
被引量:15
摘要
Underwater survey and inspection are tasks of paramount relevance for a variety of applications. They are usually performed through the employment of optical and acoustic sensors installed aboard underwater vehicles, in order to capture details of the surrounding environment. The informative properties of the data are systematically affected by a number of disturbing factors, such as the signal energy absorbed by the propagation medium or diverse noise categories contaminating the resulting imagery. Restoring the signal properties in order to exploit the carried information is typically a tough challenge. Visual saliency refers to the computational modeling of the preliminary perceptual stages of human vision, where the presence of conspicuous targets within a surveyed scene activates neurons of the visual cortex, specifically sensitive to meaningful visual variations. In relatively recent years, visual saliency has been exploited in the field of automated underwater exploration. This work provides a comprehensive overview of the computational methods implemented and applied in underwater computer vision tasks, based on the extraction of visual saliency-related features.
科研通智能强力驱动
Strongly Powered by AbleSci AI